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Article

An Enhanced Educational Competition Optimizer Integrating Multiple Mechanisms for Global Optimization Problems

1
College of Literature, Yan’an University, Yan’an 716000, China
2
School of Digital Economics, Hebi Polytechnic, Hebi 458000, China
3
School of Mathematics and Statistics, Xianyang Normal University, Xianyang 712000, China
4
Taizhou Institute of Zhejiang University, Taizhou 318000, China
*
Author to whom correspondence should be addressed.
Biomimetics 2025, 10(11), 719; https://doi.org/10.3390/biomimetics10110719 (registering DOI)
Submission received: 12 September 2025 / Revised: 10 October 2025 / Accepted: 15 October 2025 / Published: 24 October 2025

Abstract

The Educational Competition Optimizer (ECO) formulates search as a three-stage didactic process—primary, secondary and tertiary learning—but the original framework suffers from scarce information exchange, sluggish late-stage convergence and an unstable exploration–exploitation ratio. We present EECO, which introduces three synergistic mechanisms: a regenerative population strategy that uses the covariance matrix of elite solutions to maintain diversity, a Powell mechanism that accelerates exploitation within promising regions, and a trend-driven update that adaptively balances exploration and exploitation. EECO was evaluated on the 29 benchmark functions of CEC-2017 and nine real-world constrained engineering problems. Results show that EECO delivers higher solution accuracy and markedly smaller standard deviations than eight recent algorithms, including EDECO, ISGTOA, APSM-jSO, LSHADE-SPACMA, EOSMA, GLSRIME, EPSCA, and ESLPSO. Across the entire experimental battery, EECO consistently occupied the first place in the Friedman hierarchy: it attained average ranks of 2.138 in 10-D, 1.438 in 30-D, 1.207 in 50-D, and 1.345 in 100-D CEC-2017 benchmarks, together with 1.722 on the nine real-world engineering problems, corroborating its superior and dimension-scalable performance. The Wilcoxon rank sum test confirms the statistical significance of these improvements. With its remarkable convergence accuracy and reliable stability, EECO emerges as a promising variant of the ECO algorithm.

1. Introduction

Optimization requirements are ubiquitous in science and engineering decision-making. Traditional approaches rely on deterministic mathematical programming: an explicit analytical model of objectives and constraints is first formulated, after which gradient-based or enumerative methods are employed [1]. However, when problem dimensionality increases and the objective landscape becomes multimodal, non-convex, or even discontinuous, these deterministic techniques are prone to the curse of dimensionality or entrapment in local optima [2]. Over the past two decades, metaheuristic algorithms (MAs) have emerged as a prominent alternative for tackling complex optimization models, owing to their problem-agnostic framework, lenient assumptions regarding the mathematical form of the objective, and inherent robustness to noise and uncertainty [3]. Representative applications include real-time dispatching in power systems [4,5], mission planning for unmanned aerial vehicles [6,7,8], deep and machine learning [9,10], threshold selection in image segmentation [11,12], coverage optimization in wireless sensor networks [13,14], engineering optimization problems [15,16], and resource scheduling in cloud computing [17,18,19]. In parallel or distributed computing environments, MAs demonstrate favorable scalability and consistently deliver high-quality approximate optima [20,21,22].
In the early development of metaheuristic algorithms, the research community usually categorized them into three major paradigms: evolution-based, swarm-based, and physics-based algorithms [23]. Evolutionary-based metaheuristics are exemplified by Genetic Algorithm (GA) [24], Differential Evolution (DE) [25], and Evolutionary Strategies (ES) [26]. Swarm-based algorithms constitute the largest subgroup within the metaheuristic family. Classical representatives include Particle Swarm Optimization (PSO) [27] and Ant Colony Optimization (ACO) [28]. Other algorithms include Rüppell’s Fox Optimizer (RFO) [29], Greylag Goose Optimization (GGO) [30], and Parrot Optimizer (PO) [31]. Physics-inspired algorithms trace their origins to the Simulated Annealing (SA) framework introduced by Metropolis et al. in 1953 [32]. Ongoing developments in the field have produced a growing suite of algorithms grounded in physical principles, including Mirage Search Optimization (MSO) [33], Fata Morgana Algorithm (FMA) [34], and Polar Lights Optimization (PLO) [35], thereby expanding the repertoire of this category.
In recent years, new design inspirations continue to emerge, and mathematical mechanisms, plant behaviors, and human cognition have been successively abstracted into search strategies, resulting in mathematical-based algorithms, plant-based algorithms, and human-based algorithms. In addition, there are some algorithms that are difficult to categorize into any of the above categories, showing a more diversified development. Mathematics-based metaheuristics are grounded in rigorous principles such as analytical geometry, convex analysis, and game theory, giving rise to algorithms including Chaotic Evolution Optimization (CEO) [36] and Weighted Mean Of Vectors (WMOV) [37]. Plant-inspired algorithms constitute a recently emerging branch that leverages botanical metaphors—root foraging, phototropic branching, and seed dispersal—to design search operators; representative contributions include Phototropic Growth Algorithm (PGA) [38], Animated Oat Optimization (AOO) [39], and Water Uptake and Transport in Plants (WUTP) [40]. Human-based algorithms originated with the Teaching–Learning-Based Optimization (TLBO) [41]. Subsequent developments have introduced further human-centric variants, notably Information Acquisition Optimizer (IAO) [42], Enterprise Development Optimization (EDO) [43], and Football Team Training Algorithm (FTTA). In addition, there are metaphor-less metaheuristics, such as the RAO algorithm [44], the Jaya algorithm [45], the Best Mean Random (BMR) algorithm, and the Best–Worst Random (BWR) algorithm [46]. These seven categories of metaheuristic algorithms are summarized in Figure 1.
Drawing on the distinct learning phases experienced by students, Lian et al. (2024) introduced the Educational Competition Optimizer (ECO) [47]. The algorithm models three scholastic stages—primary, secondary, and tertiary—to guide population updates. Although ECO has demonstrated competitive performance on the CEC2021 benchmark suite, several limitations remain unaddressed. First, the absence of inter-population information exchange hampers the identification of promising regions during early search. Second, its convergence efficiency diminishes in later stages, preventing thorough exploitation of those regions. Third, the rigid sequential execution of the three scholastic phases induces an imbalance between exploration and exploitation. Collectively, these shortcomings restrict ECO’s capability to perform adequate global exploration and local refinement, rendering it susceptible to premature convergence on complex optimization landscapes [48]. To overcome ECO’s tendency to stagnate in local optima and its limited convergence accuracy, Emam et al. embedded a local escaping operator and a Gaussian-distribution perturbation strategy, which together enable the algorithm to jump out of premature convergence and refine the final solution quality [48]. To address these shortcomings, Tang et al. hybridized ECO with an estimation-of-distribution component and introduced a fitness–distance balance (FDB) criterion to filter individuals [49]. This combination significantly reinforces the global exploration capability of ECO while accelerating convergence efficiency. To enhance ECO’s ability to tackle complex, high-dimensional problems, Chen et al. introduced a jump strategy and an early-stopping mechanism that together accelerate convergence while maintaining exploration power [50]. This paper proposes an Enhanced Education Competition Optimizer (EECO) that integrates three complementary mechanisms: a regenerative population strategy guided by the covariance matrix of elite solutions to expand global coverage and enrich diversity; a Powell mechanism to intensify exploitation once promising areas are identified; and a trend-driven update framework that adaptively balances exploration and exploitation throughout the search process. In summary, the main contributions of this study are outlined as follows:
(1)
This study introduces an enhanced version of ECO, referred to as EECO, which incorporates the regenerative population strategy, Powell mechanism, and trend-driven update framework.
(2)
This study systematically verified the comprehensive advantages of EECO in convergence, robustness, and dimensional scalability through rigorous comparative experiments.
(3)
Multiple statistical tests, such as the Wilcoxon rank sum test, the Friedman test, and the Nemenyi post hoc test, were used to analyze the data obtained from the EECO and comparison algorithms.
This paper is partially structured as follows: Section 2 provides a comprehensive background on the ECO algorithm. Section 3 elaborates on the three new mechanisms integrated into the ECO algorithm. In Section 4, a series of comparative experiments are conducted to evaluate the EECO algorithm. Section 5 describes the application of the EECO algorithm to engineering constrained optimization problems. Section 6 summarizes the chapter and suggests directions for future research. A comprehensive schematic of the paper’s organization is presented in Figure 2.

2. Educational Competition Optimizer

The ECO algorithm takes the competitive mechanism in the education system as a metaphor and divides the optimization process in the search process into three sequential academic stages—elementary, middle, and high school. Through adaptive search strategies, ECO effects a smooth transition from global exploration to focused exploitation. Its mathematical model is summarized as follows.

2.1. Population Initialization

The ECO algorithm initializes its population via the logistic chaotic map, distinguishing itself from other metaheuristics. This map emulates social disorder arising from educational deprivation. Given population size N p o p and problem bounds l b (lower bound) and u b (upper bound), the initialization formula is expressed in Equation (1).
X i i n i = l b + u b l b × x i
In Equation (1), X i i n i denotes the initial position of the i t h agent, and x i represents the value of the logistic chaotic map, calculated by Equation (2).
x i = α × x i 1 × 1 x i 1 ,   0 x 0 1 , i = 1 , 2 , , N
where x 0 is a uniformly distributed random number in (0, 1), and α is a constant set to 4.

2.2. Primary School Stage

During the primary school stage, ECO partitions the population into two cohorts: the top 20% of individuals, ranked by fitness, form the school set, while the remaining 80% constitute the student set. Schools update their positions based on the mean location of their associated agents; students select the nearest school. This stage embodies initial exploration, with schools and students jointly surveying promising regions under constrained conditions, as formalized in Equations (3) and (4).
X i n e w = X i + ω × X i m e a n X i × L e v y D
X i n e w = X i + ω × c l o s e X i X i × r a n d n
where X i denotes the current position of the i t h agent. X i n e w denotes its updated position. X i m e a n denotes the average position of the i t h agent, as shown in Equation (5). L e v y D is a D-dimensional vector obeying the Levy distribution, in which D is the dimension of the problem. It is defined by Equation (6). c l o s e X i indicates the location of the school closest to X i . r a n d n denotes a random number drawn from the standard normal distribution. ω is a variable that changes with the number of function evaluations and is obtained from Equation (7).
X i m e a n = j = 1 D X i , j D
L e v y D = μ × σ v 2 / 3 ,   μ N 0 , D ,   v N 0 , D ,   σ = Γ 2.5 × sin 0.75 π 1.5 × Γ 1.25 × 2 0.25 2 / 3
ω = 0.1 × ln 2 F E s / F E s M a x
where F E s and F E s M a x denote the number of function evaluations and the maximum number of function evaluations, respectively.

2.3. Middle School Stage

In the middle school phase, ECO again splits the population into schools and students, now restricting schools to the top 10% of individuals by fitness while assigning the remaining 90% to the student cohort. Schools relocate by incorporating both the population mean and the best individual; students continue to select the nearest school and are additionally divided into two groups according to academic potential. These behaviors are formalized in Equations (8) and (9).
X i n e w = X i + X b e s t X m e a n × e F E s F E s M a x 1 × L e v y D
X i n e w = X i ω × c l o s e X i P × E × ω × c l o s e X i X i
where X b e s t is the best agent so far. X m e a n denotes the average position of all school agents and student agents. e denotes the natural exponential constant (Euler’s number). P denotes the patience of the student agents and is represented by Equation (10). E denotes the motivation to learn and is represented by Equation (11).
P = 4 × r a n d n × 1 F E s / F E s M a x
E = π P × F E s F E s M a x ,   r 1 > H 1 ,   r 1 H
where H is the judgment threshold with a value of 0.5. r 1 is a random variable uniformly distributed in [0, 1].

2.4. High School Stage

In the high school phase, the proportions of the two subpopulations remain identical to those in the middle school phase. School agents update their positions cautiously by integrating the average, best, and worst individuals, thereby addressing the broader needs of the student cohort. Conversely, student agents enroll in the currently top-performing school. The corresponding behaviors are formalized in Equations (12) and (13).
X i n e w = X i + X b e s t X m e a n × r a n d n X w o r s t X m e a n × r a n d n
X i n e w = X i P × E × X b e s t X i
where X w o r s t denotes the worst-performing agent observed thus far.

2.5. Selection and Greed Mechanisms

In the ECO algorithm, the three strategies are selected in rotation following the increase in iterations. Specifically, when mod(t,3) is equal to 1, all agents will select the primary-stage updating method in this round of iterations. When mod(t,3) is equal to 2, all agents will select the middle-school-stage updating method in this round of iteration. When mod(t,3) is equal to 0, all agents will select the high-school-stage updating method in this round of iteration. In addition, the ECO algorithm uses a greedy mechanism to filter the agents, which means that the agents before and after updating will be compared with each other and the better one will be kept for the next iteration.

3. Proposed Enhanced Educational Competition Optimizer

Although the ECO algorithm shows promise as a metaheuristic algorithm, it still shows limitations in complex optimization scenarios: imbalance between exploration and exploitation, susceptibility to local extremes, and insufficient convergence accuracy. In this paper, we propose the EECO algorithm, which introduces three improvements, namely regenerative population strategy, Powell mechanism, and trend-driven update framework, to balance exploration and exploitation, facilitate information exchange, and reorganize the update framework to improve the overall performance. In this section, the structure of the EECO algorithm is described in detail, followed by pseudo-code and flowcharts, and finally its computational complexity is analyzed.

3.1. Regenerative Population Strategy

Metaheuristic algorithms need to balance exploration and exploitation to achieve a comprehensive scan and accurate mining of the solution space. However, the search operators of most algorithms implicitly prefer specific regions: without being guided by the objective function, the strategies or operators may prompt the population to cluster prematurely in localized regions, resulting in overexploitation and weakening the search ability for alternative solutions. The ECO algorithm, as a human-based metaheuristic algorithm, is inevitably constrained by these same problems. In order to improve its global exploration performance and enhance the population diversity and adaptability, this paper proposes a regenerative population strategy (RPS) to make the ECO algorithm more robust in complex landscapes with low total variation, ruggedness, and needle-in-a-haystack problems. After each iteration, the RPS selects a subset of individuals for regeneration, thereby fostering continued exploration of the solution space. The proportion to be regenerated is determined jointly by current population diversity and the observed improvement rate.
Population diversity (PD), denoted as τ which quantifies the dispersion of individuals across the search space and is therefore critical for global exploration, is computed by Equation (14).
τ = i = 1 N X i X m e a n
The improvement rate (IR), denoted as ς quantifies the search progress of the population and is given by Equation (15).
ς = F X b e s t t F X b e s t t + 1 F X b e s t t + 1
Upon obtaining PD and IR, the composite score S of the current population is expressed as the normalized weighted sum of these two indices, as shown in Equation (16).
S = λ 1 × τ τ max + λ 2 × ς ς max
In the equation, τ max denotes the maximal PD observed so far, and ς max the maximal IR encountered to date. λ 1 and λ 2 are the weights assigned to the two indices. In this, both weights are set to 0.5, signifying equal importance. In the RPS, the number of individuals to be regenerated at each iteration is determined by Equation (17). Once this quantity is fixed, exactly N R P S distinct individuals—excluding the current best—are selected uniformly at random and re-initialized within the search space according to Equation (18).
N R P S = 1 S × N 1
X i = μ + g i , g i ~ N 0 , C
Here, the symbol · denotes the greatest integer function. μ is the weighted centroid of the top 50% fittest individuals, and C is the corresponding covariance matrix computed from this elite subset, capturing the population’s evolutionary trend. Each agent is assigned a weight θ proportional to its fitness, so that better-performing agents exert stronger influence on the inferred direction of evolution.
C = 2 N × i = 1 0.5 N X i μ × X i μ T
μ = 2 N × i = 1 0.5 N θ i × X i
θ i = ln 0.5 N + 1 / i = 1 0.5 N ln 0.5 N + 1 i
The RPS dynamically adjusts the number of individuals to be regenerated according to the current population quality, thereby promoting a balanced trade-off between exploitation and exploration. Moreover, the incorporation of the covariance matrix enhances population quality and strengthens global exploration.

3.2. Powell Mechanism

Excessive global exploration can degrade convergence; to restore the exploitation–exploration balance of the ECO algorithm, this work employs the Powell mechanism (PM) to intensify exploitation. Powell’s method is a potent local-search technique that exploits conjugate directions to accelerate convergence. Introduced into the late phase of ECO, it strengthens the population’s local search capacity and increases the likelihood of locating the global optimum. The procedure comprises three sequential stages: basic search, acceleration search, and adjustment search. In each iteration, basic search begins from the current position and performs one-dimensional searches along the existing directions to generate a new position vector. Acceleration search computes the difference between two consecutive position vectors to obtain a direction closer to the optimum, replacing the original search direction. Finally, adjustment search substitutes one of the current directions with the connecting direction obtained during acceleration, thereby forming a renewed direction set for the next iteration. This cycle repeats until a precise solution is attained. The specific implementation of the Powell mechanism is as follows.
Step 1: Initialization. Select an initial point γ 0 and linearly independent search directions D . Prescribe a convergence tolerance E r r > 0 and set k = 0 .
Step 2: Basic search. Compute δ i using Equation (22), then successively generate new base points γ 1 , γ 2 , …, γ D along the respective dimensions, as specified in Equation (23).
F γ i + δ i × d i = min F γ i + δ i × d i
γ i + 1 = γ i + δ i × d i ,   i = 0 , 1 , , D 1
In the equation, δ i denotes the search step sizes. If δ i is negative, a line search is performed along the corresponding axis. If i < D 1 , i is incremented by 1 and Step 2 is repeated; otherwise, Step 3 is executed.
Step 3: Acceleration search. Compute the acceleration direction d D = γ D γ 0 . If the termination criterion on d D < E r r is satisfied, exit; otherwise, proceed to Step 4.
Step 4: Compute the maximum-descent index t l using Equation (24). If Equation (25) is satisfied, the search directions for the next cycle remain unchanged, in which case set γ 0 = γ D , k = k + 1 , and proceed to Step 2; otherwise, Step 5 is executed.
F γ t l F γ t l + 1 = max 0 i D 1 F γ i F γ i + 1
F γ 0 2 × F γ D + F 2 × γ D γ 0 2 × F γ t l F γ t l + 1
Step 5: Adjusted search. Set γ t l + i = γ t l + i + 1 to ensure the newly generated exploration directions remain linearly independent, then compute δ D via Equation (22). Set γ 0 = γ D + 1 = γ D + δ D × d D , k = k + 1 , and proceed to Step 2. The PM method is used to further excavate promising regions, so PM is performed when F E s > a × F E s M a x . The parameter a will be determined in subsequent experiments.

3.3. Trend-Driven Updating Framework

ECO’s original search framework sequentially executes the elementary, middle, and high school strategies in strict cyclic order, without regard to the current population’s actual needs. This blind rotation hampers overall performance. To remedy this, we introduce a trend-driven updating framework, denoted as TUF. The TUF logs whether each agent’s previously chosen phase succeeded; success triggers reuse, while failure prompts a random switch to one of the remaining two phases. Compared with the fixed rotation, A accelerates convergence and raises optimization efficiency by favoring historically successful strategies, thereby guiding the population toward more promising regions and making better use of limited computational resources.

3.4. The Structure of EECO and Its Time Complexity

This subsection presents the detailed workflow of the proposed EECO algorithm. The algorithm first generates the initial population using a logistic chaotic map. A trend-driven updating framework then dynamically selects the appropriate stage, replacing the former iteration-based schedule. Regenerative population strategy regenerates a subset of agents to enhance global exploration, while the Powell mechanism is activated in the later phase to intensify local exploitation of promising regions. The detailed flowchart of the EECO algorithm can be found in Figure 3, and the pseudo-code is illustrated in Algorithm 1.
Algorithm 1: Pseudo-code of EECO algorithm
1: Initialize the ECO parameters
2: Initialize the population X using Equation (1)
3: While FEs < FEsMax
4: Calculate the fitness function
5: Find the best position and worst position
6: Randomly select one strategy to update each agent
7: Execute strategy according to the value of St
8: For i = 1: N do
9:      If St = 1 Then // Stage 1: Primary school
10:      Update each agent using Equations (3) and (4)
11:    End if
12:    If St = 2 Then // Stage 2: Middle school
13:      Update each agent using Equations (8) and (9)
14:    End if
15:    If St = 3 Then // Stage 3: High school
16:      Update each agent using Equations (12) and (13)
17:    End if
18: End for
19: Update the St using trend-driven updating framework // TDUF
20: FEs = FEs + N
21: Update some agent using regenerative population strategy // RPS
22: If FEs > 0.9 × FEsMax Then
23: Update the best agent using Powell mechanism // PM
24: FEs = FEs + mxit2
25: End if
26: End while
27: Return the best solution
This paper integrates three improvement mechanisms based on the basic ECO algorithm, so it is necessary to analyze the time complexity of the proposed EECO algorithm. According to the literature [47], the time complexity of the ECO algorithm consists of three parts: population initialization, fitness computation, and position update strategy. Assuming that the number of populations is N , the problem dimension is D , and the number of iterations is T , then the time complexity of the ECO algorithm is O N × D + T × N × D + T × N × log N . For the EECO algorithm, there is no change in the initialization phase and the three update strategies, so there is no increase in time complexity for this part. Assuming that the RPS replaces N 1 agents, the time complexity of this part is O T × N 1 × D + T × N 1 × log N 1 . The time complexity of the PM is O T × m x i t 2 , where A denotes that it is executed m x i t times. The TDUF changes the selection framework of the original strategies, and it does not involve additional location updates and adaptation calculations, so there is no increase in time complexity. In conclusion, the time complexity of the EECO algorithm is O N × D + T × N + N 1 × D + T × N × log N + N 1 × log N 1 + T × m x i t 2 .

4. Numerical Experiments Using the CEC-2017 Test Set

In this section, we comprehensively evaluate the performance of the EECO algorithm on the CEC-2017 test set. Section 4.1 describes the experimental setup and details of the CEC-2017 test set. A parameter sensitivity analysis is performed in Section 4.2 to determine the optimal parameter settings for the EECO algorithm. Section 4.3 provides the results of the ablation experiments. In Section 4.4, we examine the structural bias of both the EECO and ECO algorithms. In Section 4.5, a comprehensive comparison between the EECO algorithm and several advanced algorithms is presented.

4.1. Experimental Settings and Descriptions of Benchmark Functions

All experiments were conducted on a 2.50 GHz AMD R9-7945HX CPU with 32 GB RAM and an RTX 4060 GPU, under Windows 11 and MATLAB 2023a. For every benchmark test function, the maximum number of function evaluations was set to 1000D, and each algorithm was run independently 30 times to mitigate stochastic variability.
Benchmark functions are indispensable for evaluating algorithmic performance and provide a standardized platform for comparing diverse optimization methods. To comprehensively assess the capabilities of the proposed EECO algorithm, we adopt the CEC-2017 test suite at dimensions 10, 30, 50, and 100. Increasing dimensionality entails a rapid proliferation of local optima, thereby imposing a more stringent test on global search ability. The CEC-2017 suite comprises 29 functions categorized into four classes: unimodal (F1–F2), multimodal (F3–F9), hybrid (F10–F19), and composition (F20–F29). Unimodal functions possess a single global optimum and no local optima, making them suitable for gauging exploitation intensity. Multimodal functions contain numerous local optima and are primarily used to evaluate an algorithm’s capacity to locate the global optimum and to escape local basins. Hybrid and composition functions emulate highly intricate continuous landscapes, thereby assessing the combined ability of an algorithm to perform both local refinement and global exploration. Detailed specifications of all functions are provided in Table 1. The complete mathematical formulation is available in Reference [51].
During the experimental section, the best value (Best), the average value (Ave), the standard deviation (Std), and the ranking (Rank) obtained by all the algorithms on each of the CEC-2017 functions were fully documented. Given that detailed tables would significantly increase the length of the main text, the raw data have been transferred to the Appendix A. In the main section, we dissect these results primarily using the Wilcoxon rank sum test, the Friedman test, and the Nemenyi post hoc test. The Wilcoxon rank sum test is used to pairwise compare the results of two algorithms over the full range of test functions to determine which performs better in a statistically significant way, while the Friedman test is used for the entire experimental group to comprehensively assess whether the differences between all algorithms at the overall level are significant. If the Friedman test shows significant differences, the Nemenyi post hoc test further utilizes a critical difference plot to pinpoint specific gaps between the algorithms. It should be emphasized that all statistical tests set the significance level α to 0.05 to ensure the reliability of the conclusions.

4.2. Parameter Sensitivity Analysis

4.2.1. The Analysis of Parameter N

Appropriate population sizing is a decisive factor in unlocking the full potential of metaheuristic algorithms. Operating under a fixed budget for function evaluations, these optimizers must deliver high-quality solutions within limited resources; consequently, identifying a parsimonious yet sufficient population size becomes critical. If the size is too large, the computational resources will be unnecessarily consumed in the early stage; if the size is too small, it is difficult to cover the entire solution space, and both will compromise the performance of the algorithm. Moreover, the proposed RPS relies on the covariance matrix of the elite sub-population to infer evolutionary directions. If the number of individuals is insufficient, the sample noise will overwhelm the true distribution, leading to overfitting of the covariance matrix, and the algorithm is prone to falling into local extremes or generating oscillations, with a consequent weakening of the global exploration capability. Hence, RPS imposes its sensitivity window on population magnitude. Under a uniform cap on function evaluations, this section systematically examines the performance of the EECO algorithm across population sizes of 5D, 10D, 15D, 20D, 25D, and 30D, accounting for problem dimensions ranging from 10D to 100D. Comprehensive results on the CEC-2017 test suite are tabulated in Table A1, Table A2, Table A3 and Table A4 of Appendix A, while Figure 4 depicts the corresponding Friedman average rankings, revealing the impact of population scaling on algorithmic efficacy.
As Figure 4 illustrates, the performance of the EECO algorithm first deteriorates and then improves as the population size increases, confirming that both undersized and oversized populations are detrimental. Overall, the EECO algorithm attains its best results with a population of 15D, yielding an average Friedman rank of 2.215. Moreover, the ranking curves across different dimensions exhibit a consistent pattern, validating the dimension-scaled population sizing adopted herein. Consequently, all subsequent experiments employ a population size of 15D to fully exploit the capabilities of the EECO algorithm.

4.2.2. The Analysis of Parameter a

This work introduces the PM method only in the later search phase to perform high-precision, fast-converging local refinement around the incumbent solutions. Nevertheless, PM’s reliance on conjugate-direction searches renders it less effective on high-dimensional, ill-conditioned, or non-convex problems: its cost grows rapidly with dimensionality, and as a purely local method, it lacks any mechanism for escaping local optima once trapped. Consequently, PM is not employed throughout the entire optimization run. Algorithm 1 activates it only when a predefined progress indicator signals that exploitation is warranted. To determine the most advantageous activation point, we examine the EECO under various threshold values on the CEC-2017 benchmark suite; the resulting statistics are consolidated in Table A5, Table A6, Table A7 and Table A8 of Appendix A, and the corresponding Friedman average ranks are visualized in Figure 5 to illustrate how the timing of PM engagement influences overall algorithmic performance.
Figure 5 reveals that the later the PM is activated, the better the EECO performs. This observation aligns with our analysis: premature invocation of the Powell mechanism elevates computational overhead and hampers overall efficiency, whereas deferring its use safeguards exploratory breadth. Consequently, the activation threshold a is fixed at 0.8, enabling PM only during the final 20% of the search budget to conduct intensified exploitation of promising basins.

4.3. Strategy Effectiveness Analysis

The EECO algorithm augments the original ECO by integrating three complementary mechanisms: a regenerative population strategy (RPS), the Powell mechanism (PM), and a trend-driven update framework (TDUF). To quantify the individual contribution of each component, we conduct a systematic ablation study using six EECO variants whose configurations are summarized in Table 2. In this table, the first row lists the variant labels, and the first column enumerates the adopted strategies; “Yes” indicates inclusion, whereas “No” denotes exclusion of the corresponding mechanism. Such experiments play a pivotal role in verifying the robustness and dependability of research findings. By selectively excluding specific components or factors and observing the resulting changes in performance, researchers can better isolate the effects of each mechanism, thus eliminating alternative explanations. This process helps to clarify the individual contribution of each component, ensuring that the conclusions drawn are both valid and reproducible.
The ablation-study results for the EECO algorithm are consolidated in Table A9, Table A10, Table A11 and Table A12 of Appendix A. Table 3 summarizes the Friedman test results for EECO against its ablated variants, and the corresponding ranking is visually presented in Figure 6. A statistically significant difference exists between EECO and the compared variants, as indicated by the p-values in the final column. In light of these Friedman outcomes, the following conclusions can be drawn. (1) Across four-dimensional settings, the fully integrated EECO—employing all three enhancement strategies—achieves the best overall performance, attaining mean Friedman ranks of 1.741, 1.172, 1.241, and 1.138, respectively. (2) When ECO is compared with its single-strategy variants, all three improvements prove individually effective. (3) Among the variants that omit exactly one component, the rank ordering indicates that the RPS contributes most to EECO’s performance, followed by the PM, while the TDUF yields the smallest incremental gain. (4) A dimension-wise comparison reveals that TDUF is largely insensitive to increasing dimensionality, demonstrating strong scalability; conversely, RPS and PM confer greater benefits in lower-dimensional problem instances.
To quantify the individual contributions of the three strategies to ECO, a Nemenyi post hoc test was conducted, with the results shown in Figure 7. This test extends the Friedman finding of an overall difference by computing the critical difference value (CDV) via Equation (26), where M denotes the number of algorithms and K the number of benchmark functions. According to Nemenyi’s criterion, any pair of algorithms whose average ranks differ by less than CDV are not significantly different. Figure 7 reveals that EECO is not significantly different from ECO-RT at 10D and 30D, indicating that TDUF provides limited improvement in low-dimensional cases. Similarly, ECO-T does not differ significantly from ECO across all four-dimensional settings, implying that TDUF’s enhancement, while beneficial, is modest. Finally, the three two-strategy variants of ECO exhibit no significant pairwise differences, confirming that the strategies act synergistically rather than restrictively.
C D V = q a × K K + 1 6 M
Moreover, this section assesses the scalability of EECO by contrasting its performance with that of the basic ECO across multiple dimensional settings of the CEC-2017 benchmark. Scalability analysis is instrumental in understanding how an evolutionary algorithm adapts to increasing problem size and complexity. By systematically varying dimensionality, we evaluate the algorithm’s ability to maintain both efficiency and solution quality under escalating computational demands. The tests examine computational cost, execution time, and solution accuracy, thereby offering detailed insights into the practical feasibility and inherent limitations when tackling large-scale optimization tasks. Such evaluation is crucial for validating real-world applicability, as scalable algorithms are better suited for the high-dimensional, complex problems ubiquitous in industrial and engineering domains. Summarized in Table 3, the results reveal that EECO consistently outperforms ECO across all tested dimensions, demonstrating its robustness and adaptability in large-scale optimization scenarios. Table 4 presents the Wilcoxon rank sum test results between EECO, its ablated variants, and the baseline ECO, where the symbols “+/=/−” indicate the number of functions on which EECO or its variants outperform, match, or underperform ECO. The data reveal that neither RPS nor TDUF degrades ECO’s performance on any function, whereas PM alone occasionally worsens the outcome. Once PM is coupled with either RPS or TDUF, no further inferior results are observed, confirming that RPS and TDUF possess sufficient transferability to compensate for PM’s deficiencies. Consequently, all three proposed enhancement mechanisms are validated as effective.

4.4. Structural Bias Analysis of EECO

Structural bias is a common flaw in metaheuristic algorithms, referring to the tendency of an algorithm to favor solutions in specific regions of the search space [52]. In this subsection we investigate the structural bias exhibited by the EECO and ECO algorithms using the center–offset method (CO). Specifically, we conduct the experiment on the Griewank function and shift its global optimum according to Equation (27). The function dimensions are 30 and 100.
f x , c = 1 + 1 4000 j = 1 D x j c j 2 j = 1 D cos x j c j j
where c = c 1 , c 2 , , c D represents the coordinate of the new center. The results of 30 independent runs on this function for both the EECO and ECO algorithms are reported in Table 5. According to Table 5, the ECO algorithm attains its highest accuracy when c = 100 , 100 , , 100 , indicating a pronounced preference for boundary regions. In contrast, the EECO algorithm achieves the best results when c = 0 , 0 , , 0 and c = 100 , 100 , , 100 , and performs comparably well in the remaining three cases. Overall, EECO exhibits no evident structural bias.

4.5. Comparative Analysis with Other Algorithms

This subsection benchmarks EECO against seven advanced algorithms—EDECO, ISGTOA [53], APSM-jSO [54], LSHADE-SPACMA [55], EOSMA [56], GLSRIME [57], EPSCA [58], and ESLPSO [59]—on the CEC-2017 test suite. To ensure impartiality, all competing algorithms are configured exactly as reported in their original publications, with parameter values listed in Table 6; any remaining experimental settings follow the specifications given in Section 4.1. Comprehensive evaluation is undertaken via the Wilcoxon rank sum test, Friedman test, Nemenyi post hoc test, convergence analysis, and robustness analysis. All raw numerical results are compiled in Table A13, Table A14, Table A15 and Table A16 of Appendix A.
Table 7 summarizes the Wilcoxon rank sum test results between EECO and the competing state-of-the-art algorithms, where “+” denotes that EECO significantly outperforms the rival, “−” indicates the opposite, and “=” signifies no statistically significant difference. Across all pairwise comparisons, EECO accumulates far more “+” than “−” or “=”, evidencing its consistent superiority across the benchmark functions and thereby corroborating its robustness and efficiency in tackling complex optimization tasks. The detailed analysis of the Wilcoxon rank sum test is presented below.
For 10D, EECO is superior (inferior) to EDECO, ISGTOA, APSM-jSO, LSHADE-SPACMA, EOSMA, GLSRIME, EPSCA, and ESLPSO on 25(0), 25(0), 23(2), 23(2), 23(2), 23(1), 21(0), and 24(1) test functions. That is, the EECO algorithm is dominant in at least 21 functions when compared to different algorithms when solving CEC-2017 test functions with 10D.
For 30D, EECO is superior (inferior) to EDECO, ISGTOA, APSM-jSO, LSHADE-SPACMA, EOSMA, GLSRIME, EPSCA, and ESLPSO on 29(0), 29(0), 26(3), 26(2), 29(0), 28(0), 25(2), and 26(2) test functions. That is, the EECO algorithm is dominant in at least 25 functions when compared to different algorithms when solving CEC-2017 test functions with 30D.
For 50D, EECO is superior (inferior) to EDECO, ISGTOA, APSM-jSO, LSHADE-SPACMA, EOSMA, GLSRIME, EPSCA, and ESLPSO on 29(0), 29(0), 27(2), 27(2), 29(0), 29(0), 23(0), and 27(1) test functions. That is, the EECO algorithm is dominant in at least 23 functions when compared to different algorithms when solving the CEC-2017 test functions with 50D.
For 100D, EECO is superior (inferior) to EDECO, ISGTOA, APSM-jSO, LSHADE-SPACMA, EOSMA, GLSRIME, EPSCA, and ESLPSO on 29(0), 28(0), 24(2), 24(2), 29(0), 27(0), 21(0), and 24(2) test functions. That is, the EECO algorithm is dominant in at least 21 functions when compared to different algorithms when solving CEC-2017 test functions with 100D.
The Friedman test results for EECO against competing algorithms on the CEC-2017 benchmark are depicted in Figure 8. Across all dimensional settings, EECO consistently secures the first position, attaining mean ranks of 2.138, 1.483, 1.207, and 1.345 for 10D, 30D, 50D, and 100D, respectively. The p-values reported in the last column of Table 8 confirm the presence of statistically significant differences among the algorithms. To quantify the magnitude of these differences, a Nemenyi post hoc analysis—described in Section 4.3—is applied, with the outcomes illustrated in Figure 9. On 10D functions, no significant difference is detected between EECO and LSHADE-SPACMA; likewise, EECO and EPSCA are statistically indistinguishable on 50-D and 100-D functions. In all remaining pairwise comparisons, the CDV segments do not connect EECO to any competing algorithm, indicating that EECO is significantly superior to those counterparts.
Figure 10 illustrates the convergence profiles of EECO alongside the competing algorithms. Convergence curves are indispensable for tracking the optimization trajectory, as they allow direct inspection of both convergence speed and final accuracy, thereby exposing common pitfalls such as premature stagnation or oscillatory behavior. By visualizing the evolution of fitness values, researchers can appraise the efficiency of each method and make informed parameter adjustments to enhance performance. These plots also serve as diagnostic instruments for assessing how well an algorithm adapts to varying problem complexities, rendering them an integral component of algorithmic design and performance evaluation. In this subsection, convergence curves are provided for six representative test functions—unimodal F1, multimodal F6, hybrid F13 and F18, and composite F22 and F28—where the x-axis denotes the number of fitness evaluations and the y-axis presents the corresponding fitness values.
The results indicate that the EECO algorithm exhibits clear advantages in these functions, achieving fast convergence and maintaining the lowest objective values among the compared algorithms. Even in the more challenging hybrid and combinatorial functions, the EECO algorithm consistently delivers competitive or superior optimization results, reflecting its robustness across a wide range of problem environments. The excellent convergence efficiency of the EECO algorithm on unimodal functions is attributed to the further exploitation of the optimal solution by the PM strategy. The RPS creatively resets part of the population, which improves the quality of the population and facilitates the finding of more promising regions, which in turn enhances the exploration capability of the EECO algorithm. This is the reason why the EECO algorithm performs well on multimodal functions. The TDUF allows each individual to choose a strategy that favors them based on the search process, achieving a balance between exploitation and exploration. Hybrid and composite functions examine the balance of an algorithm, and TDUF improves the performance of the EECO algorithm on complex functions. The covariance matrix of RPS fits the direction of population evolution better, which also enhances the performance of the EECO algorithm on hybrid and composite functions.
Figure 11 provides the distribution of solutions provided by the EECO algorithms and the comparison algorithms in the face of the CEC-2017 test set, represented by a box plot. The box plots can show median, interquartile range (IQR), and outliers simultaneously, reflecting the concentration trend, dispersion, and extreme performance of each algorithm. The outliers and box lengths quickly identify whether an algorithm is experiencing performance fluctuations or crashes, and are more resistant to outlier interference than the mean alone. In the box plot, the lower and narrower the box as a whole indicates that the algorithm converges with high accuracy and stability. In this subsection, box plots are drawn for the six test functions (unimodal F1, multimodal F6, hybrid F13 and F18, and composite F22 and F28) where the x-axis denotes each algorithm and the y-axis denotes the corresponding fitness values. It is evident from Figure 11 that the EECO algorithm shows more robustness and stability compared to its competitors. Figure 8 clearly reveals that EECO exhibits superior robustness and stability relative to its competitors, demonstrating that the proposed enhancements bolster performance without compromising reliability. The EECO algorithm shows less fluctuation in different box plots which validates its stable performance.
Additionally, to examine the impact of different population sizes, we compare the EECO algorithm with the competing algorithms on 30-D functions in this subsection. The population sizes of the competing algorithms are set according to their original papers, and the results are presented in Table 9.
According to Table 9, EECO achieves the best Friedman rank of 1.414, whereas the original ECO algorithm ranks last with a Friedman score of 8.241. Regardless of whether the same population size or the size recommended in the original literature is used, EECO’s advantage remains clear. The Wilcoxon rank sum test shows that EECO’s performance gap versus EDECO and GLSRIME is unchanged, its margin over APSM-jSO and LSHADE-SPACMA has widened, and its lead over ISGTOA, EOSMA, EPSCA, and ESLPSO has narrowed slightly.
Collectively, the experimental evidence demonstrates that EECO comprehensively surpasses the compared methods on the CEC-2017 test suite, thereby exhibiting high reliability and exceptional adaptability in addressing global optimization problems.

5. Numerical Experiments Using Constrained Engineering Optimization Problems

This section evaluates EECO’s capability to address real-world engineering challenges by applying it to ten well-established constrained optimization problems, detailed in Table 10. Since metaheuristic algorithms were initially designed to solve unconstrained optimization problems, it is necessary to transform constrained optimization problems into unconstrained optimization problems. A common constraint handling method is the penalty function method. Specifically, during fitness evaluation, any candidate solution that violates one or more constraints is penalized by adding a penalty term to its objective value, thereby ensuring that it is progressively discarded owing to its elevated fitness in subsequent iterations.
Table 11 provides a comprehensive comparison between EECO and the competing algorithms, detailing each method’s Friedman rank and the outcomes of Wilcoxon pairwise contrasts with EECO. Figure 12 complements this by presenting a radar chart of the rankings across all functions; the area enclosed by each algorithm’s polygon inversely quantifies its relative performance, with smaller areas denoting superior efficacy. According to Table 11, the EECO algorithm stands out with a Friedman ranking of 1.722. In Figure 12, the EECO algorithm encloses the smallest surface, reflecting its robustness and efficiency on engineering constrained optimization problems. The number of “+/=/−” reveals the superior performance of the EECO algorithm compared to other algorithms on the 10 engineering constraint optimization problems. Although individual algorithms outperform the EECO algorithm on some problems, most of the results show the strong competitiveness of the EECO algorithm. In conclusion, the performance of the EECO algorithm in 10 engineering constrained optimization problems is good, and these results further validate the broad application prospects of the EECO algorithm in various engineering and scientific real-world problems, making it one of the core optimization tools in the field.

6. Conclusions

In this work, we propose an enhanced variant of the Educational Competition Optimizer—termed EECO—which augments the original ECO algorithm by synergistically integrating three mechanisms: a regenerative population strategy, the Powell mechanism, and a trend-driven update framework, thereby substantially strengthening its search capability. The regenerative population strategy elevates population quality and markedly enhances the global exploration capability of the ECO algorithm. The Powell mechanism refines the local search procedure, contributing to further gains in convergence efficiency. The trend-driven update framework dynamically balances exploitation and exploration throughout the search process. To evaluate the effectiveness of the proposed EECO, comprehensive and extensive experiments were conducted. First, optimal parameter settings were systematically investigated on the CEC-2017 benchmark. Second, ablation studies confirmed that each enhancement contributes positively to performance and that the algorithm scales well. Comparative assessments against a suite of state-of-the-art metaheuristics further corroborate EECO’s superior efficacy. Finally, successful application to real-world constrained engineering problems underscores its practical utility. Despite its demonstrated strengths, the EECO algorithm still exhibits limitations that warrant further investigation. First, the parameter space examined in this study is restricted; more extensive and fine-grained parameter analyses are required. Second, the Powell mechanism incurs additional computational expense in high-dimensional problems, necessitating a more sophisticated activation criterion than the current iteration-based trigger. Finally, the strategy-selection mechanism itself remains amenable to refinement to mitigate mis-selections induced by premature convergence.
Looking ahead, we will pursue three complementary lines of research. First, we will develop advanced regenerative-population strategies that replace the current random selection of individuals for regeneration with adaptive, quality-aware rules—an extension expected to further strengthen algorithmic performance. Second, we will engineer a binary variant of the EECO algorithm to address a broad class of discrete optimization problems. Thirdly, we will investigate the theoretical convergence properties of the EECO algorithm, rather than relying solely on convergence curves [60]. Finally, we will integrate EECO with cutting-edge techniques from artificial intelligence, such as reinforcement-learning-based selection of search mechanisms [61], large-language-model-assisted design of improved search operators [62], and the incorporation of fuzzy-set theory for handling uncertainty [63].

Author Contributions

Conceptualization, N.L. and Z.L.; Data curation, N.L., S.Z. and M.W.; Formal analysis, Z.M., S.Z. and M.W.; Funding acquisition, Z.L.; Investigation, S.Z. and H.Z.; Methodology, N.L. and Z.L.; Project administration, Z.L.; Resources, S.Z. and H.Z.; Software, N.L. and Z.M.; Supervision, Z.L.; Validation, Z.M.; Visualization, Z.M., H.Z. and M.W.; Writing—original draft, N.L.; Writing—review and editing, N.L. and Z.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by a Project Supported by the Scientific Research Fund of Zhejiang Provincial Education Department, grant number Y202352110.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data is provided within the manuscript.

Acknowledgments

I would like to thank the anonymous reviewers who have helped to improve the paper.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. Experiments comparing EECO with different population sizes (10D).
Table A1. Experiments comparing EECO with different population sizes (10D).
No.IndexN = 5DN = 10DN = 15DN = 20DN = 25DN = 30D
F1Best4.8595E+041.0763E+029.4699E+023.9914E+031.9278E+048.4037E+03
Avg1.9123E+066.1492E+031.7517E+044.8399E+054.9668E+057.9832E+06
Std4.3461E+067.6330E+034.2886E+047.7810E+055.5473E+059.6802E+06
Rank512346
F2Best3.0242E+023.0000E+023.0001E+023.0024E+023.0190E+023.0086E+02
Avg3.0229E+034.0358E+023.0347E+027.9393E+023.5153E+023.9217E+02
Std3.7665E+032.3704E+021.0456E+011.8443E+031.2587E+021.4431E+02
Rank641523
F3Best4.0058E+024.0180E+024.0346E+024.0486E+024.0285E+024.0504E+02
Avg4.1157E+024.0516E+024.0503E+024.0560E+024.0605E+024.0717E+02
Std2.4411E+011.8355E+009.7697E-016.1410E-011.3397E+002.2543E+00
Rank621345
F4Best5.0612E+025.0301E+025.1582E+025.1504E+025.0594E+025.1237E+02
Avg5.2157E+025.1216E+025.2575E+025.2907E+025.2476E+025.2828E+02
Std8.6368E+006.4400E+005.6800E+007.4053E+007.5196E+009.2499E+00
Rank214635
F5Best6.0295E+026.0001E+026.0018E+026.0081E+026.0061E+026.0202E+02
Avg6.0909E+026.0202E+026.0043E+026.0183E+026.0218E+026.0454E+02
Std4.5711E+003.3227E+003.6358E-017.7587E-011.2081E+001.6609E+00
Rank631245
F6Best7.1924E+027.1620E+027.2143E+027.3322E+027.2249E+027.2952E+02
Avg7.3863E+027.2902E+027.3799E+027.4284E+027.4257E+027.4279E+02
Std1.2719E+011.0369E+017.6167E+005.5781E+008.9606E+001.0005E+01
Rank312645
F7Best8.0340E+028.0510E+028.1230E+028.1695E+028.0941E+028.2126E+02
Avg8.1352E+028.1147E+028.2517E+028.2651E+028.2581E+028.3387E+02
Std6.1569E+005.0650E+005.5161E+007.0147E+009.7016E+008.8162E+00
Rank213546
F8Best9.1818E+029.0000E+029.0000E+029.0030E+029.0003E+029.0150E+02
Avg1.0713E+039.0940E+029.0073E+029.1313E+029.0675E+029.0810E+02
Std1.5316E+022.3728E+011.8366E+004.6510E+016.5648E+009.6271E+00
Rank641523
F9Best1.4081E+031.6475E+031.7746E+032.1070E+031.9598E+031.5376E+03
Avg2.1563E+032.1775E+032.2668E+032.4329E+032.4066E+032.2734E+03
Std4.1512E+023.3064E+022.8930E+022.5572E+022.8808E+023.0560E+02
Rank123654
F10Best1.1071E+031.1048E+031.1035E+031.1069E+031.1068E+031.1069E+03
Avg1.1681E+031.1226E+031.1155E+031.1132E+031.1257E+031.1241E+03
Std5.9867E+011.3765E+011.2798E+014.7963E+004.2826E+011.3995E+01
Rank632154
F11Best2.3525E+031.3422E+031.5929E+032.8385E+033.6268E+033.6692E+03
Avg1.6594E+065.8179E+034.5646E+051.6254E+052.1813E+041.2329E+05
Std5.4052E+068.1754E+031.7416E+065.6720E+051.9068E+042.0884E+05
Rank615423
F12Best1.3787E+031.3516E+031.3372E+031.3406E+031.3669E+031.6952E+03
Avg2.4121E+031.6045E+031.5285E+031.5196E+031.7626E+033.2664E+03
Std1.1576E+033.5796E+022.2942E+022.1092E+022.6638E+022.9867E+03
Rank532146
F13Best1.4230E+031.4041E+031.4164E+031.4192E+031.4225E+031.4245E+03
Avg1.4371E+031.4261E+031.4281E+031.4287E+031.4290E+031.4385E+03
Std1.0260E+019.9050E+006.9769E+003.9787E+004.6537E+007.2611E+00
Rank512346
F14Best1.5063E+031.5002E+031.5032E+031.5091E+031.5095E+031.5089E+03
Avg1.6518E+031.5285E+031.5204E+031.5216E+031.5234E+031.5526E+03
Std1.5990E+021.7736E+011.8269E+011.0545E+019.5723E+004.2394E+01
Rank641235
F15Best1.6023E+031.6049E+031.6176E+031.6545E+031.6148E+031.6136E+03
Avg1.7508E+031.6427E+031.6565E+031.7184E+031.6937E+031.7261E+03
Std2.6290E+025.7058E+013.1351E+015.3756E+017.0774E+017.2044E+01
Rank612435
F16Best1.7261E+031.7287E+031.7485E+031.7472E+031.7590E+031.7683E+03
Avg1.7576E+031.7640E+031.7701E+031.7858E+031.7780E+031.7929E+03
Std4.0995E+011.8687E+011.4271E+012.1839E+011.4121E+012.0678E+01
Rank123546
F17Best1.8450E+031.8279E+031.8271E+031.8555E+031.9132E+031.9449E+03
Avg6.4087E+031.8997E+031.8840E+031.9201E+032.0905E+033.1689E+03
Std7.0102E+038.1512E+018.6589E+017.1315E+011.4029E+022.0460E+03
Rank621345
F18Best1.9064E+031.9025E+031.9040E+031.9053E+031.9059E+031.9071E+03
Avg2.0149E+031.9076E+031.9061E+031.9073E+031.9097E+031.9189E+03
Std3.4349E+025.3305E+002.0609E+001.3595E+002.3615E+009.3895E+00
Rank631245
F19Best2.0227E+032.0264E+032.0591E+032.0740E+032.0266E+032.0700E+03
Avg2.0862E+032.0718E+032.0955E+032.1293E+032.1215E+032.1232E+03
Std4.6870E+012.9628E+013.5544E+013.6273E+014.2822E+014.0521E+01
Rank213645
F20Best2.2062E+032.2056E+032.2066E+032.2044E+032.2089E+032.2059E+03
Avg2.2872E+032.3081E+032.2943E+032.2911E+032.2939E+032.2802E+03
Std4.8298E+012.9635E+014.1245E+015.7039E+014.7961E+015.2861E+01
Rank265341
F21Best2.2431E+032.3000E+032.2121E+032.2265E+032.2157E+032.2172E+03
Avg2.3085E+032.3028E+032.2846E+032.3037E+032.2876E+032.3099E+03
Std2.0642E+013.3049E+003.3724E+012.1425E+013.5405E+012.7207E+01
Rank531426
F22Best2.6059E+032.6053E+032.6074E+032.6160E+032.6156E+032.6234E+03
Avg2.6319E+032.6192E+032.6225E+032.6286E+032.6301E+032.6329E+03
Std2.5433E+012.4610E+011.2546E+017.2161E+001.4344E+017.2166E+00
Rank512346
F23Best2.7347E+032.7295E+032.6808E+032.5246E+032.6111E+032.5780E+03
Avg2.7513E+032.7385E+032.7449E+032.7381E+032.7373E+032.7449E+03
Std1.8318E+017.4868E+001.8709E+016.0590E+014.4556E+015.0939E+01
Rank634215
F24Best2.8984E+032.8978E+032.8977E+032.8980E+032.8990E+032.8983E+03
Avg2.9514E+032.9346E+032.9286E+032.9213E+032.9340E+032.9360E+03
Std4.2770E+012.0191E+013.5185E+013.5084E+011.9936E+011.9592E+01
Rank642135
F25Best2.9572E+032.9000E+032.9002E+032.9027E+032.9024E+032.9113E+03
Avg3.1784E+032.9908E+032.9230E+032.9129E+032.9270E+032.9430E+03
Std1.2692E+021.0853E+023.9557E+011.2724E+012.8823E+012.6207E+01
Rank652134
F26Best3.0909E+033.0894E+033.0894E+033.0909E+033.0911E+033.0929E+03
Avg3.1142E+033.1005E+033.0991E+033.1041E+033.0970E+033.0994E+03
Std2.6483E+011.5908E+011.6515E+012.4439E+014.1964E+007.7354E+00
Rank642513
F27Best3.2654E+033.1778E+033.1687E+033.1550E+033.1859E+033.3073E+03
Avg3.4302E+033.3868E+033.3706E+033.3722E+033.3821E+033.4074E+03
Std6.8223E+018.1829E+019.8072E+018.3396E+016.6498E+013.0778E+01
Rank641235
F28Best3.1360E+033.1509E+033.1556E+033.1782E+033.1633E+033.1534E+03
Avg3.2112E+033.1934E+033.2025E+033.2137E+033.2209E+033.2122E+03
Std6.0581E+013.3077E+013.2331E+012.1876E+013.3264E+013.2422E+01
Rank312564
F29Best6.2676E+033.6511E+033.7610E+033.7521E+033.6571E+034.0333E+03
Avg4.1484E+053.2335E+056.3152E+055.8273E+052.8142E+053.4140E+05
Std3.5198E+054.9806E+051.0372E+061.1270E+064.6953E+055.1143E+05
Rank426513
Table A2. Experiments comparing EECO with different population sizes (30D).
Table A2. Experiments comparing EECO with different population sizes (30D).
No.IndexN = 5DN = 10DN = 15DN = 20DN = 25DN = 30D
F1Best1.5604E+081.3040E+082.8527E+078.0355E+072.2776E+071.8340E+08
Avg5.8038E+088.7446E+081.0271E+091.5151E+091.1717E+091.0333E+09
Std5.0604E+089.6859E+081.7790E+093.7248E+091.5368E+098.7883E+08
Rank123654
F2Best1.1317E+041.4841E+031.9051E+032.7909E+032.4060E+034.3986E+03
Avg2.3386E+041.0503E+046.8564E+037.6498E+031.3168E+042.0606E+04
Std7.4206E+036.1297E+034.0857E+033.4909E+039.7080E+031.1551E+04
Rank631245
F3Best5.4119E+025.1888E+024.9059E+025.1834E+025.3091E+025.7505E+02
Avg6.1301E+025.8922E+026.0134E+026.6104E+025.7188E+026.3798E+02
Std4.6609E+015.0844E+011.6387E+023.3517E+022.2214E+014.7859E+01
Rank423615
F4Best5.4283E+025.8542E+026.4876E+026.4931E+025.6765E+026.0920E+02
Avg6.1443E+026.3281E+026.8004E+026.9432E+026.7135E+026.9280E+02
Std7.9029E+013.0437E+011.9930E+013.1447E+014.2186E+013.6702E+01
Rank124635
F5Best6.1392E+026.0406E+026.0684E+026.0732E+026.0933E+026.1060E+02
Avg6.2299E+026.1523E+026.1264E+026.1410E+026.1672E+026.1775E+02
Std5.0377E+008.1328E+005.4919E+004.0379E+005.5846E+004.3634E+00
Rank631245
F6Best8.5511E+028.8794E+028.8462E+029.0581E+028.4331E+028.4672E+02
Avg9.9101E+029.7510E+029.2254E+029.4390E+029.5705E+029.5618E+02
Std6.8207E+018.3866E+012.8961E+011.7563E+014.3010E+017.8214E+01
Rank651243
F7Best8.4591E+028.6841E+029.3928E+029.6960E+029.3160E+028.8010E+02
Avg8.8813E+029.3524E+029.8227E+029.9258E+029.9147E+029.8928E+02
Std2.5532E+013.9806E+012.3951E+011.6915E+012.9661E+013.6585E+01
Rank123654
F8Best1.6977E+039.2417E+029.7128E+021.0698E+039.6668E+021.0217E+03
Avg2.5489E+031.5250E+031.2863E+031.5792E+031.4166E+031.6933E+03
Std6.2017E+025.3642E+022.7043E+029.1685E+022.9582E+026.9480E+02
Rank631425
F9Best5.3758E+035.2068E+037.0759E+036.8100E+036.0362E+036.6660E+03
Avg7.0225E+037.6316E+038.0889E+038.1154E+038.1760E+037.9800E+03
Std8.6244E+021.0318E+035.5973E+026.6878E+028.0857E+026.8917E+02
Rank124563
F10Best1.2490E+031.1509E+031.2037E+031.2156E+031.2694E+031.3064E+03
Avg1.3188E+031.2248E+031.2827E+031.3098E+031.3486E+031.4151E+03
Std6.7948E+015.2918E+011.0807E+024.4154E+016.3011E+018.5768E+01
Rank412356
F11Best3.0107E+064.6772E+043.5878E+051.4575E+063.9047E+061.9433E+06
Avg1.0593E+079.9443E+067.7752E+061.0803E+072.0711E+072.7741E+07
Std6.7296E+062.1709E+071.5554E+077.0419E+061.7790E+072.5011E+07
Rank321456
F12Best1.7214E+047.9647E+032.4240E+045.0770E+042.6545E+044.0316E+04
Avg5.4048E+042.1485E+045.4911E+042.7292E+052.8330E+057.4577E+05
Std2.7645E+048.1477E+032.0264E+042.6970E+052.7192E+051.4089E+06
Rank213456
F13Best1.4808E+031.4743E+031.5180E+031.5915E+031.6267E+031.6892E+03
Avg2.0138E+031.5108E+031.5740E+031.7817E+031.9262E+033.9942E+03
Std1.6235E+032.5961E+013.4393E+011.4430E+022.1465E+023.0659E+03
Rank512346
F14Best2.7911E+031.9056E+032.1998E+031.3694E+042.2146E+042.2301E+04
Avg7.9350E+037.1264E+038.8400E+033.6136E+045.2094E+042.4587E+05
Std5.0792E+031.1887E+048.6126E+031.9553E+042.4432E+045.6188E+05
Rank213456
F15Best1.8317E+032.0407E+032.4629E+032.6047E+032.6467E+032.2475E+03
Avg2.1995E+032.4978E+032.9451E+033.0294E+033.1000E+032.9671E+03
Std1.9949E+023.0874E+022.8682E+022.2533E+022.7303E+023.3334E+02
Rank123564
F16Best1.7740E+031.8379E+031.8650E+031.9674E+031.8358E+031.8888E+03
Avg1.8564E+031.9268E+032.1045E+032.1453E+032.1486E+032.1424E+03
Std8.2958E+013.8987E+011.8707E+021.2063E+021.5134E+021.9424E+02
Rank123564
F17Best5.9045E+032.0245E+032.3376E+033.8728E+032.2364E+046.1198E+04
Avg1.5561E+058.5094E+035.4309E+031.7540E+048.9240E+041.3365E+05
Std4.7033E+059.7862E+033.2327E+039.5388E+031.1937E+051.1395E+05
Rank621345
F18Best2.0851E+031.9795E+032.2630E+033.7107E+032.0000E+046.0360E+03
Avg1.3088E+045.4627E+033.7883E+032.9988E+041.4128E+052.5832E+05
Std1.2913E+049.4141E+031.7637E+033.7110E+042.5631E+052.8918E+05
Rank321456
F19Best2.0986E+032.1835E+032.3893E+032.4547E+032.3678E+032.3740E+03
Avg2.2323E+032.4538E+032.6138E+032.6426E+032.6682E+032.6826E+03
Std1.1902E+021.8509E+021.2031E+021.3946E+021.7310E+021.3974E+02
Rank123456
F20Best2.3508E+032.3851E+032.3928E+032.4391E+032.3831E+032.3854E+03
Avg2.3800E+032.4509E+032.4557E+032.4746E+032.4768E+032.4716E+03
Std2.1028E+013.6727E+012.8925E+012.0134E+013.5183E+013.8136E+01
Rank123564
F21Best2.5081E+032.4322E+032.4519E+032.3823E+032.6968E+032.6734E+03
Avg3.3833E+032.9802E+033.7365E+033.5237E+035.6600E+034.8598E+03
Std1.3608E+034.8885E+021.4409E+031.7393E+032.3060E+032.8346E+03
Rank214365
F22Best2.7286E+032.7267E+032.7939E+032.8104E+032.7720E+032.7831E+03
Avg2.7927E+032.8003E+032.8377E+032.8542E+032.8638E+032.8540E+03
Std7.3466E+018.7791E+012.8745E+013.2981E+013.6222E+013.4499E+01
Rank123564
F23Best2.8550E+032.8849E+032.9748E+032.9894E+032.8951E+032.9191E+03
Avg2.9284E+032.9820E+033.0171E+033.0391E+033.0465E+033.0710E+03
Std6.1813E+019.4234E+014.6858E+016.5024E+017.3058E+019.9490E+01
Rank123456
F24Best2.9071E+032.9027E+032.9100E+032.9039E+032.9194E+032.9204E+03
Avg2.9996E+032.9605E+032.9345E+032.9589E+032.9643E+032.9796E+03
Std1.3307E+025.2971E+014.7959E+016.9244E+014.2420E+016.4235E+01
Rank631245
F25Best3.9323E+033.4467E+033.3116E+033.2177E+033.7531E+033.9780E+03
Avg5.0752E+034.3811E+035.2204E+035.5065E+035.3894E+035.8562E+03
Std8.4249E+024.2678E+027.6924E+021.1569E+038.0678E+021.1979E+03
Rank213546
F26Best3.2091E+033.2122E+033.2233E+033.2225E+033.2484E+033.2339E+03
Avg3.2535E+033.2563E+033.2488E+033.2629E+033.2798E+033.3005E+03
Std2.4776E+013.1958E+012.5436E+012.9647E+013.0476E+013.5567E+01
Rank231456
F27Best3.2944E+033.2924E+033.2752E+033.2582E+033.3172E+033.2883E+03
Avg3.4422E+033.3908E+033.3592E+033.3613E+033.4108E+033.4209E+03
Std1.6191E+026.6476E+018.3898E+016.2604E+019.2250E+016.9247E+01
Rank631245
F28Best3.4629E+033.6460E+033.6488E+033.6903E+033.9916E+033.9825E+03
Avg3.9013E+033.9208E+034.0779E+034.0993E+034.1891E+034.2964E+03
Std4.2733E+022.5566E+023.8359E+022.3003E+021.5830E+022.1895E+02
Rank123456
F29Best4.1986E+041.1403E+043.0712E+041.7256E+051.6194E+052.4405E+05
Avg5.7659E+053.4796E+051.3357E+054.4427E+058.6013E+051.9325E+06
Std1.0967E+068.0472E+051.9060E+052.3675E+058.2743E+051.4268E+06
Rank421356
Table A3. Experiments comparing EECO with different population sizes (50D).
Table A3. Experiments comparing EECO with different population sizes (50D).
No.IndexN = 5DN = 10DN = 15DN = 20DN = 25DN = 30D
F1Best1.0464E+093.0916E+093.0551E+093.4913E+092.9233E+093.5045E+09
Avg5.3003E+091.0807E+107.7470E+098.0086E+096.5863E+091.1258E+10
Std3.3646E+091.1003E+104.5052E+094.0377E+093.7751E+091.4812E+10
Rank153426
F2Best9.3818E+031.5159E+043.7782E+043.1256E+042.9531E+043.6406E+04
Avg2.4396E+043.1732E+046.3519E+044.6336E+046.1068E+047.0945E+04
Std1.0754E+047.5513E+031.0586E+041.3716E+041.8353E+042.5185E+04
Rank125346
F3Best6.7676E+027.6014E+029.2967E+028.8521E+028.1978E+029.1823E+02
Avg1.0692E+031.1221E+031.2453E+031.4739E+031.3279E+032.2201E+03
Std6.1460E+023.8068E+023.3289E+028.4955E+026.0864E+021.7009E+03
Rank123546
F4Best7.9446E+027.6121E+026.6515E+028.5128E+027.8145E+027.8113E+02
Avg8.8007E+028.5906E+027.2696E+029.0908E+029.1426E+028.8905E+02
Std4.2654E+013.8750E+014.0949E+013.5782E+015.6573E+015.7904E+01
Rank321564
F5Best6.1612E+026.1310E+026.2326E+026.2206E+026.2159E+026.2574E+02
Avg6.2510E+026.2827E+026.3251E+026.3263E+026.3366E+026.3677E+02
Std4.1335E+001.2796E+016.3796E+009.7574E+008.5906E+001.0287E+01
Rank123456
F6Best1.0281E+031.1373E+031.1504E+031.0759E+031.0770E+039.3922E+02
Avg1.2091E+031.2487E+031.2743E+031.2334E+031.2226E+031.2671E+03
Std1.2049E+029.7427E+017.8379E+019.3537E+017.2183E+011.6243E+02
Rank146325
F7Best1.0680E+031.0602E+039.2196E+021.1466E+031.1100E+039.7816E+02
Avg1.1722E+031.1593E+031.0525E+031.2239E+031.2077E+031.2231E+03
Std5.0224E+015.8248E+017.7442E+016.8215E+014.8648E+018.7720E+01
Rank321645
F8Best3.4203E+033.3504E+034.3891E+033.2046E+032.9019E+032.2207E+03
Avg6.0036E+035.3840E+031.1629E+046.3592E+036.0796E+036.4834E+03
Std3.4545E+032.3850E+033.8736E+034.3122E+033.0466E+032.8936E+03
Rank216435
F9Best9.2837E+039.3511E+039.0986E+031.3835E+041.1737E+048.2585E+03
Avg1.3580E+041.2659E+041.2253E+041.4623E+041.3777E+041.3716E+04
Std1.5399E+031.3701E+031.7768E+035.3864E+021.1344E+032.0576E+03
Rank321654
F10Best1.3938E+031.3416E+031.5074E+031.4966E+031.3672E+031.4306E+03
Avg1.4900E+031.7548E+031.6914E+031.7216E+031.6999E+031.7913E+03
Std6.1770E+015.3185E+021.8264E+023.5154E+021.8644E+021.9036E+02
Rank152436
F11Best9.2151E+062.0131E+072.6027E+071.2509E+077.2572E+079.8213E+07
Avg4.5971E+071.3835E+081.2548E+081.7365E+082.2453E+088.4313E+08
Std2.4595E+071.7825E+081.1190E+081.2774E+081.0895E+081.9636E+09
Rank132456
F12Best5.3806E+041.6819E+042.6321E+042.7742E+051.1725E+057.0723E+04
Avg2.1842E+055.2744E+041.7059E+055.6583E+065.5632E+061.4207E+07
Std1.5405E+052.2185E+044.2624E+056.5812E+066.0665E+061.9591E+07
Rank312546
F13Best1.6787E+031.6482E+031.6296E+031.9081E+034.8425E+034.0291E+03
Avg2.3773E+031.0836E+047.6438E+037.3343E+033.9322E+046.1703E+04
Std1.5488E+033.5310E+041.2179E+045.3973E+033.3461E+046.0806E+04
Rank143256
F14Best4.6681E+033.0440E+032.8158E+031.7606E+041.4419E+048.3681E+03
Avg2.7817E+046.8582E+031.1374E+047.0331E+056.2676E+056.0336E+05
Std2.2540E+043.4194E+037.5199E+037.9233E+059.6788E+051.5888E+06
Rank312654
F15Best3.3297E+032.3292E+032.1006E+033.1098E+033.3113E+034.2440E+03
Avg4.0126E+033.2417E+032.5834E+034.3022E+034.2646E+034.6942E+03
Std4.7291E+026.0733E+022.6591E+024.7459E+026.2150E+023.2460E+02
Rank321546
F16Best2.8939E+032.5164E+032.1418E+032.7366E+032.9775E+033.1205E+03
Avg3.4015E+033.2039E+032.5893E+033.6512E+033.6385E+033.8370E+03
Std2.7264E+023.7580E+022.3182E+023.8490E+022.8816E+023.4040E+02
Rank321546
F17Best9.8506E+033.3850E+031.2409E+044.6311E+046.4508E+047.8028E+04
Avg3.2867E+041.2764E+062.0844E+051.2440E+052.5216E+053.7391E+05
Std1.9536E+044.3526E+063.7748E+055.0930E+041.5727E+051.8865E+05
Rank163245
F18Best1.1956E+042.1591E+035.8497E+033.0800E+043.0345E+042.6560E+04
Avg3.5456E+041.9431E+041.6560E+042.2830E+053.9427E+054.4979E+05
Std3.9304E+044.4321E+048.2289E+032.3759E+055.9353E+057.5544E+05
Rank321456
F19Best3.3973E+032.6651E+032.1819E+033.3636E+032.9016E+033.0525E+03
Avg3.6828E+033.3172E+032.5859E+033.7605E+033.5540E+033.6115E+03
Std1.7216E+023.0118E+023.0101E+022.0677E+024.0841E+023.7600E+02
Rank521634
F20Best2.4986E+032.5207E+032.4348E+032.4586E+032.5492E+032.5202E+03
Avg2.6460E+032.5923E+032.5007E+032.6611E+032.6698E+032.6835E+03
Std4.9408E+013.8341E+013.8190E+016.5735E+015.1278E+015.8277E+01
Rank321456
F21Best3.6946E+031.2033E+049.1883E+031.4486E+041.3422E+041.2342E+04
Avg1.4801E+041.4784E+041.2171E+041.5646E+041.5295E+041.5147E+04
Std3.1531E+031.3040E+032.1954E+038.0426E+029.4400E+021.3927E+03
Rank321654
F22Best3.0688E+033.0165E+032.9311E+033.0711E+033.0468E+033.0746E+03
Avg3.1764E+033.1404E+033.0365E+033.1847E+033.2301E+033.2644E+03
Std9.3939E+019.6981E+016.4226E+015.6424E+017.9354E+018.8665E+01
Rank321456
F23Best3.1152E+033.1493E+033.0572E+033.2403E+033.2102E+033.3183E+03
Avg3.2956E+033.2853E+033.3328E+033.3968E+033.3820E+033.5209E+03
Std1.4672E+021.0366E+023.0120E+021.7779E+021.1968E+022.3534E+02
Rank213546
F24Best3.1664E+033.1706E+033.1268E+033.2322E+033.2895E+033.3186E+03
Avg3.7473E+033.4845E+033.4524E+033.6424E+033.6854E+033.5727E+03
Std9.9627E+023.3974E+021.9600E+028.0083E+029.6101E+021.9396E+02
Rank621453
F25Best5.0901E+034.8387E+034.8268E+034.5970E+036.7452E+036.5360E+03
Avg7.6361E+037.6369E+037.6120E+037.6965E+038.5982E+038.6682E+03
Std2.0392E+031.7365E+031.8050E+031.4762E+031.7689E+031.1779E+03
Rank231456
F26Best3.5313E+033.3750E+033.5478E+033.5080E+033.5229E+033.6488E+03
Avg3.7563E+033.7340E+033.8769E+033.6937E+033.8525E+033.9255E+03
Std2.2633E+022.5745E+022.4764E+021.4404E+022.3954E+022.1873E+02
Rank325146
F27Best3.4811E+033.6121E+033.7378E+033.6171E+033.5609E+033.7847E+03
Avg3.9157E+034.0797E+034.3366E+034.2002E+034.2898E+034.4358E+03
Std4.4185E+025.7788E+029.4325E+027.3072E+025.8283E+024.6252E+02
Rank125346
F28Best4.3194E+034.0313E+033.7405E+034.5073E+034.4327E+034.8778E+03
Avg4.9161E+034.4880E+034.4059E+035.0906E+035.0526E+035.3316E+03
Std2.7640E+023.8673E+025.4027E+023.2549E+023.8052E+024.0370E+02
Rank321546
F29Best1.2056E+074.6847E+063.7770E+061.9966E+072.0389E+072.8353E+07
Avg1.6003E+071.3920E+071.2476E+072.8806E+073.4954E+075.7312E+07
Std4.7722E+068.5395E+065.1979E+066.9741E+061.0557E+071.6429E+07
Rank321456
Table A4. Experiments comparing EECO with different population sizes (100D).
Table A4. Experiments comparing EECO with different population sizes (100D).
No.IndexN = 5DN = 10DN = 15DN = 20DN = 25DN = 30D
F1Best2.7424E+103.0968E+102.7495E+102.3895E+102.4130E+103.1645E+10
Avg4.4130E+105.8942E+104.1016E+106.0823E+104.2234E+104.7684E+10
Std1.4819E+102.9826E+109.9627E+093.5880E+101.3624E+101.1848E+10
Rank351624
F2Best6.7138E+048.6366E+041.3358E+058.0065E+041.2236E+051.0682E+05
Avg1.1729E+051.1374E+051.6201E+051.7541E+052.2434E+051.9414E+05
Std2.3725E+041.3889E+041.5676E+044.2043E+045.0457E+046.0866E+04
Rank213465
F3Best2.8108E+033.0741E+033.0844E+033.4000E+032.9105E+032.9078E+03
Avg5.4631E+035.5275E+034.6179E+035.3604E+035.0295E+035.3793E+03
Std3.5381E+034.9257E+031.3133E+032.0167E+032.4151E+031.4562E+03
Rank561324
F4Best1.3154E+031.1481E+031.0068E+031.2614E+031.1603E+039.4633E+02
Avg1.4464E+031.4168E+031.1181E+031.5260E+031.4750E+031.4546E+03
Std6.7499E+011.3672E+029.0432E+011.0989E+021.2540E+022.0673E+02
Rank321654
F5Best6.2727E+026.3656E+026.3700E+026.3902E+026.4173E+026.3622E+02
Avg6.4468E+026.4664E+026.4812E+026.5393E+026.5107E+026.5735E+02
Std1.2014E+016.6575E+009.1135E+001.0088E+015.8974E+001.0451E+01
Rank123546
F6Best1.8813E+031.8761E+032.1588E+031.8276E+031.7677E+031.8381E+03
Avg2.0754E+032.3754E+032.4122E+032.2432E+032.1310E+032.1230E+03
Std1.3942E+024.5267E+021.6876E+024.1488E+021.9126E+022.0851E+02
Rank156432
F7Best1.5475E+031.6299E+031.4184E+031.7225E+031.5943E+031.3741E+03
Avg1.7774E+031.7349E+031.6069E+031.8639E+031.8652E+031.8136E+03
Std1.1006E+027.6319E+011.4096E+021.2829E+021.1927E+021.7620E+02
Rank321564
F8Best1.1040E+041.3008E+042.0610E+041.4648E+041.7776E+041.5389E+04
Avg1.8543E+042.1323E+043.2922E+042.0647E+042.3444E+042.7835E+04
Std8.9386E+035.9535E+039.9816E+033.0739E+034.3438E+031.0002E+04
Rank136245
F9Best2.7277E+042.4461E+041.9896E+042.6308E+042.0836E+042.3208E+04
Avg2.9595E+042.8976E+042.6372E+043.0256E+042.9536E+042.9939E+04
Std1.0632E+031.5836E+033.2734E+031.2940E+032.8161E+032.2931E+03
Rank421635
F10Best3.8263E+034.7783E+039.0616E+037.7991E+037.3580E+039.9601E+03
Avg5.5642E+037.2523E+031.3501E+041.0857E+041.2398E+041.7791E+04
Std1.2877E+032.3123E+033.6198E+032.3240E+033.1906E+035.1209E+03
Rank125346
F11Best3.5322E+083.0289E+089.9015E+081.3562E+091.3291E+091.8839E+09
Avg1.7146E+092.0433E+092.0248E+096.0440E+092.8868E+098.5157E+09
Std7.5608E+081.8903E+097.5303E+081.0686E+101.2851E+091.0470E+10
Rank132546
F12Best1.7646E+054.4467E+044.7572E+053.3105E+052.2444E+066.0832E+06
Avg6.2341E+078.9911E+055.5354E+061.2441E+083.7394E+072.5383E+08
Std2.2817E+082.8723E+067.2221E+062.0676E+083.8052E+075.9431E+08
Rank412536
F13Best6.4071E+031.9937E+032.0940E+037.0230E+048.2505E+041.6272E+05
Avg2.9614E+059.0557E+033.5874E+043.1959E+055.4612E+057.6278E+05
Std9.1873E+051.8196E+041.0303E+053.4296E+054.0678E+055.5985E+05
Rank312456
F14Best3.0459E+042.3567E+041.6075E+045.4906E+041.5094E+054.4770E+04
Avg9.5486E+064.3846E+041.5619E+058.7603E+068.2069E+067.5711E+07
Std3.4679E+071.3152E+042.5901E+057.4531E+061.3201E+072.2572E+08
Rank512436
F15Best7.4498E+035.8129E+034.0486E+038.4723E+037.1670E+037.2910E+03
Avg8.7536E+037.3314E+034.9125E+039.4798E+039.1767E+039.1983E+03
Std6.2581E+029.5695E+021.1495E+036.4022E+029.4374E+021.0226E+03
Rank321645
F16Best5.8807E+034.5149E+032.9141E+036.3810E+035.2269E+035.2125E+03
Avg6.6045E+035.8587E+033.7514E+036.8512E+036.9234E+036.9761E+03
Std4.2444E+026.0854E+024.2169E+023.7580E+025.9571E+021.0512E+03
Rank321456
F17Best7.0872E+042.3135E+044.5388E+046.3515E+042.5016E+053.8803E+05
Avg1.2727E+052.0645E+053.3767E+051.6586E+065.1464E+059.9208E+05
Std5.6413E+045.0653E+057.6165E+054.3100E+062.0929E+056.1496E+05
Rank123645
F18Best4.6670E+054.1251E+044.9532E+043.5587E+066.5170E+053.0289E+06
Avg2.2325E+063.6478E+054.7194E+058.5298E+071.5612E+073.2480E+07
Std2.5526E+063.8973E+054.9518E+052.8740E+081.7119E+072.1318E+07
Rank312645
F19Best4.7946E+034.9490E+033.5711E+036.1426E+035.5446E+035.1262E+03
Avg6.1535E+036.3453E+035.6038E+036.8657E+036.5441E+036.5858E+03
Std7.8239E+026.1734E+028.0650E+024.1745E+025.8776E+028.3253E+02
Rank231645
F20Best3.0644E+032.9418E+032.9295E+033.2837E+033.1794E+033.1473E+03
Avg3.2476E+033.2312E+033.0014E+033.3643E+033.3496E+033.3877E+03
Std8.7357E+011.0565E+026.1309E+014.3471E+018.5855E+011.1763E+02
Rank321546
F21Best2.9361E+042.8697E+042.4900E+043.2012E+042.9016E+042.5937E+04
Avg3.2480E+043.1661E+042.9452E+043.3402E+043.3101E+043.1812E+04
Std1.2865E+031.6274E+032.7142E+039.0638E+021.3543E+032.2313E+03
Rank421653
F22Best3.4921E+033.5301E+033.4506E+033.8355E+033.8621E+033.7367E+03
Avg3.9566E+034.0000E+033.8616E+034.0799E+034.1848E+034.2368E+03
Std1.7212E+023.3333E+023.9590E+021.6790E+021.5746E+023.3100E+02
Rank231456
F23Best4.2560E+034.2306E+033.9076E+034.3594E+034.3743E+034.4600E+03
Avg5.1306E+034.7821E+034.5290E+034.7587E+034.9304E+035.3968E+03
Std7.6657E+025.9035E+023.5939E+023.0000E+023.6679E+027.5880E+02
Rank531246
F24Best4.1692E+035.2789E+035.3113E+034.9554E+034.8405E+035.1824E+03
Avg5.6078E+035.8588E+036.0214E+036.7563E+035.7237E+036.1900E+03
Std1.8595E+035.0606E+024.7341E+022.7107E+035.8016E+027.0538E+02
Rank134625
F25Best1.3059E+041.3291E+041.0277E+049.2088E+031.6261E+041.5577E+04
Avg2.0002E+041.9832E+041.6042E+041.9631E+042.2143E+042.1181E+04
Std5.2108E+035.7504E+032.2874E+036.3450E+036.7575E+035.0131E+03
Rank431265
F26Best3.7274E+033.7020E+033.9083E+034.1078E+034.2458E+033.9833E+03
Avg4.2223E+034.1909E+034.1651E+034.5435E+034.7845E+034.6682E+03
Std4.0082E+023.6374E+022.6607E+024.7865E+024.7883E+023.4158E+02
Rank321465
F27Best4.5786E+035.9173E+035.9007E+036.3944E+035.5418E+037.2794E+03
Avg8.1156E+038.7979E+037.4144E+038.7920E+039.2086E+031.0376E+04
Std2.5880E+033.0476E+038.6071E+021.6567E+034.1532E+033.0861E+03
Rank241356
F28Best7.9974E+037.0598E+036.6154E+038.9851E+038.9387E+039.8518E+03
Avg9.0509E+038.6145E+037.2790E+031.0078E+041.0372E+041.1322E+04
Std7.6525E+028.3251E+024.3452E+026.4818E+026.9294E+027.9124E+02
Rank321456
F29Best1.1347E+073.8130E+065.3980E+066.7692E+071.3742E+081.2327E+08
Avg4.6708E+076.3340E+072.4786E+073.4457E+082.5812E+082.6304E+08
Std2.7969E+071.7160E+081.8235E+075.6307E+081.3436E+081.1693E+08
Rank231645
Table A5. Experiments comparing EECO with different parameter a s (10D).
Table A5. Experiments comparing EECO with different parameter a s (10D).
No.IndexECOa = 0.5a = 0.6a = 0.7a = 0.8a = 0.9
F1Best6.3568E+061.0000E+021.0000E+021.0000E+021.0000E+021.0000E+02
Avg1.5632E+081.0004E+021.0000E+021.0015E+021.0000E+021.0000E+02
Std3.1359E+081.3750E-012.3854E-075.8681E-012.1836E-072.0234E-07
Rank641532
F2Best7.2490E+023.0000E+023.0000E+023.0000E+023.0000E+023.0000E+02
Avg3.1268E+033.0000E+023.0000E+023.0000E+023.0000E+023.0000E+02
Std2.1573E+031.8695E-111.0756E-112.4836E-117.4740E-122.7136E-11
Rank632415
F3Best4.0663E+024.0000E+024.0000E+024.0000E+024.0000E+024.0000E+02
Avg4.2652E+024.0000E+024.0000E+024.0000E+024.0000E+024.0000E+02
Std2.3682E+011.4492E-138.9440E-134.5829E-131.2855E-122.4948E-12
Rank614235
F4Best5.1504E+025.1492E+025.0895E+025.0696E+025.0696E+025.0696E+02
Avg5.4079E+025.3098E+025.2972E+025.2978E+025.2912E+025.2680E+02
Std1.4548E+011.9987E+011.7686E+011.8452E+011.8853E+011.8017E+01
Rank653421
F5Best6.0731E+026.0995E+026.0694E+026.0643E+026.0516E+026.0578E+02
Avg6.2141E+026.1782E+026.1501E+026.1395E+026.1352E+026.1254E+02
Std9.6906E+005.9686E+005.8454E+004.7690E+005.9790E+005.8255E+00
Rank654321
F6Best7.2950E+027.1403E+027.1403E+027.1789E+027.1789E+027.1789E+02
Avg7.6287E+027.5129E+027.4851E+027.4684E+027.4524E+027.4411E+02
Std1.8573E+011.7442E+011.6104E+011.4205E+011.3200E+011.3109E+01
Rank654321
F7Best8.1459E+028.0995E+028.0995E+028.0995E+028.0995E+028.0995E+02
Avg8.3687E+028.2229E+028.2295E+028.2235E+028.2235E+028.2235E+02
Std9.3431E+008.6803E+009.0993E+009.1874E+009.1874E+009.1874E+00
Rank615224
F8Best9.2354E+029.1561E+029.1540E+029.0486E+029.1734E+029.0961E+02
Avg1.0787E+031.1089E+031.0707E+031.0544E+031.0789E+031.0680E+03
Std1.2133E+021.6866E+021.1160E+021.1246E+021.4738E+021.4369E+02
Rank463152
F9Best1.6251E+031.5237E+031.2540E+031.2540E+031.2540E+031.2540E+03
Avg2.0675E+031.9178E+031.7884E+031.7925E+031.7952E+031.8071E+03
Std3.3508E+022.1044E+022.8604E+022.9603E+022.6213E+022.6405E+02
Rank651234
F10Best1.1602E+031.1216E+031.1216E+031.1209E+031.1209E+031.1216E+03
Avg1.2608E+031.1836E+031.1737E+031.1757E+031.1761E+031.1746E+03
Std9.8558E+014.9742E+014.5508E+014.6263E+014.5928E+014.0861E+01
Rank651342
F11Best9.6759E+041.3460E+031.2112E+031.3585E+031.3186E+031.3186E+03
Avg4.9010E+061.7013E+031.5941E+031.6350E+032.1391E+032.0787E+03
Std6.3820E+061.8958E+022.2521E+021.0398E+021.5224E+036.7431E+02
Rank631254
F12Best1.9964E+031.3853E+031.3248E+031.5295E+031.4370E+031.5049E+03
Avg1.5972E+041.8783E+031.7995E+031.8864E+031.8507E+031.9453E+03
Std1.8296E+043.0653E+022.9808E+023.0359E+023.1223E+022.3976E+02
Rank631425
F13Best1.4708E+031.4339E+031.4315E+031.4348E+031.4341E+031.4352E+03
Avg1.5422E+031.4802E+031.5067E+031.4912E+031.4893E+031.4892E+03
Std8.5245E+013.2990E+018.1397E+015.2430E+013.9156E+013.4019E+01
Rank615432
F14Best1.6616E+031.5022E+031.5015E+031.5035E+031.5035E+031.5052E+03
Avg2.5911E+031.5958E+031.6046E+031.5968E+031.6003E+031.6116E+03
Std1.0180E+039.5218E+019.8870E+019.0882E+016.0997E+016.6745E+01
Rank614235
F15Best1.6103E+031.6012E+031.6012E+031.6014E+031.6014E+031.6014E+03
Avg1.7834E+031.6853E+031.6906E+031.6918E+031.6999E+031.6927E+03
Std1.0502E+028.2294E+018.5838E+017.6911E+018.5837E+017.7187E+01
Rank612354
F16Best1.7553E+031.7301E+031.7286E+031.7286E+031.7308E+031.7286E+03
Avg1.7989E+031.7643E+031.7635E+031.7612E+031.7631E+031.7633E+03
Std4.2116E+014.1763E+013.0504E+012.9553E+013.0365E+013.0083E+01
Rank654123
F17Best2.8667E+031.8346E+031.8263E+031.8231E+031.8265E+031.8265E+03
Avg2.0116E+041.8813E+031.8956E+031.8755E+031.8945E+031.8899E+03
Std1.5720E+043.8931E+015.4760E+015.3272E+017.5361E+018.2343E+01
Rank625143
F18Best1.9546E+031.9086E+031.9173E+031.9179E+031.9150E+031.9132E+03
Avg3.0823E+031.9760E+031.9733E+031.9860E+031.9786E+031.9762E+03
Std1.8128E+034.7324E+014.0777E+014.5941E+014.0846E+015.2675E+01
Rank621543
F19Best2.0621E+032.0375E+032.0379E+032.0393E+032.0390E+032.0395E+03
Avg2.1270E+032.1068E+032.0896E+032.0858E+032.0841E+032.0808E+03
Std4.6113E+014.5178E+013.3625E+013.1574E+013.6869E+013.2887E+01
Rank654321
F20Best2.2086E+032.2000E+032.2000E+032.2000E+032.2024E+032.2000E+03
Avg2.2536E+032.2602E+032.2618E+032.2597E+032.2599E+032.2598E+03
Std5.2251E+016.4014E+016.6419E+016.3548E+016.3311E+016.3435E+01
Rank156243
F21Best2.2577E+032.2261E+032.2261E+032.2116E+032.2116E+032.2261E+03
Avg2.3184E+032.2991E+032.2948E+032.2956E+032.2966E+032.2928E+03
Std2.8828E+012.4555E+013.2214E+013.2918E+013.6065E+012.7818E+01
Rank652341
F22Best2.6198E+032.6149E+032.6121E+032.6115E+032.6115E+032.6115E+03
Avg2.6346E+032.6264E+032.6248E+032.6245E+032.6239E+032.6239E+03
Std1.9097E+019.6911E+009.7082E+001.0282E+019.8880E+009.8901E+00
Rank654312
F23Best2.5475E+032.5000E+032.5000E+032.5000E+032.5000E+032.5000E+03
Avg2.7375E+032.7221E+032.7186E+032.7204E+032.7204E+032.7204E+03
Std6.7204E+019.2320E+018.9605E+019.1787E+019.1787E+019.1787E+01
Rank651432
F24Best2.9133E+032.8980E+032.8980E+032.8977E+032.8978E+032.8980E+03
Avg2.9530E+032.9352E+032.9358E+032.9364E+032.9363E+032.9363E+03
Std2.3641E+012.2379E+012.2636E+012.1658E+012.3095E+012.3348E+01
Rank612543
F25Best2.9206E+032.6000E+032.6000E+032.6000E+032.6000E+032.6000E+03
Avg3.1026E+033.0497E+033.0374E+033.0345E+033.0110E+033.0121E+03
Std1.0755E+021.8396E+021.8157E+021.9442E+021.8356E+021.8422E+02
Rank654312
F26Best3.0914E+033.0889E+033.0838E+033.0880E+033.0884E+033.0841E+03
Avg3.1013E+033.0980E+033.0962E+033.0949E+033.0945E+033.0928E+03
Std1.1701E+011.8074E+011.0668E+014.7820E+004.9097E+004.8664E+00
Rank654321
F27Best3.1801E+033.1000E+033.1000E+033.1000E+033.1000E+033.1000E+03
Avg3.4163E+033.2662E+033.2643E+033.2566E+033.2530E+033.2588E+03
Std1.3588E+025.4372E+015.3608E+015.6318E+015.4080E+015.0822E+01
Rank654213
F28Best3.1753E+033.1555E+033.1477E+033.1472E+033.1488E+033.1488E+03
Avg3.2381E+033.2308E+033.2357E+033.2287E+033.2309E+033.2265E+03
Std4.2469E+017.0588E+017.1072E+016.1748E+017.1347E+016.2751E+01
Rank635241
F29Best1.9416E+043.3158E+033.2318E+033.2658E+033.2322E+033.2737E+03
Avg8.0401E+053.7135E+033.4197E+033.3965E+033.4133E+033.3686E+03
Std7.4313E+051.0255E+032.2074E+021.4140E+021.3867E+028.6409E+01
Rank654231
Table A6. Experiments comparing EECO with different parameter a s (30D).
Table A6. Experiments comparing EECO with different parameter a s (30D).
No.IndexECOa = 0.5a = 0.6a = 0.7a = 0.8a = 0.9
F1Best1.4202E+091.0000E+021.0000E+021.0000E+021.0000E+021.0000E+02
Avg5.2751E+091.0000E+021.0000E+021.0023E+021.0000E+021.0000E+02
Std3.8240E+094.0702E-075.4950E-067.4310E-016.4302E-071.8528E-05
Rank623514
F2Best3.8187E+043.0000E+023.0000E+023.0000E+023.0000E+023.0000E+02
Avg5.3594E+043.0000E+023.0000E+023.0000E+023.0000E+023.0000E+02
Std1.1290E+048.6284E-075.3625E-079.9798E-071.0239E-061.3597E-06
Rank641532
F3Best9.1908E+024.0000E+024.0000E+024.0000E+024.0000E+024.0000E+02
Avg1.2338E+034.0239E+024.0319E+024.0279E+024.0279E+024.0319E+02
Std2.7164E+022.0587E+001.6809E+001.9257E+001.9257E+001.6809E+00
Rank615324
F4Best6.7284E+025.6766E+025.7562E+025.7462E+025.7263E+025.7562E+02
Avg7.4774E+026.6954E+026.6825E+026.6994E+026.6775E+026.6894E+02
Std4.4218E+016.2440E+016.1067E+016.0381E+016.1221E+016.0235E+01
Rank642513
F5Best6.3203E+026.3027E+026.3028E+026.2677E+026.1978E+026.1952E+02
Avg6.5026E+026.4077E+026.4029E+026.3998E+026.3838E+026.3744E+02
Std1.1109E+016.9300E+006.7559E+007.1047E+008.0791E+008.3091E+00
Rank654321
F6Best1.0318E+038.9463E+028.9993E+029.0147E+028.9855E+028.4193E+02
Avg1.1395E+031.0182E+039.9774E+029.9754E+029.9667E+029.8756E+02
Std6.9933E+011.2117E+021.2158E+021.2146E+021.2113E+021.2815E+02
Rank654321
F7Best9.4569E+028.9950E+028.9751E+028.9751E+028.9054E+028.9154E+02
Avg1.0338E+039.4994E+029.4715E+029.4745E+029.4556E+029.4616E+02
Std4.1974E+013.3172E+013.0989E+013.1090E+013.2468E+013.2364E+01
Rank653412
F8Best4.0687E+031.8912E+031.9147E+031.8923E+031.8841E+031.8940E+03
Avg7.1373E+033.7637E+033.7640E+033.7625E+033.7536E+033.7692E+03
Std1.7726E+031.2705E+031.2663E+031.2667E+031.2724E+031.2570E+03
Rank634215
F9Best7.0669E+033.9684E+033.9684E+033.7607E+033.7607E+033.6619E+03
Avg7.6756E+035.1046E+035.1429E+034.9384E+035.0141E+034.9202E+03
Std4.9056E+025.4236E+027.2399E+027.9556E+028.6859E+027.3501E+02
Rank645231
F10Best1.5595E+031.1716E+031.1677E+031.1677E+031.1677E+031.1677E+03
Avg2.7350E+031.2293E+031.2296E+031.2193E+031.2307E+031.2279E+03
Std1.0929E+034.2976E+015.3487E+013.7497E+014.9668E+014.4332E+01
Rank634152
F11Best4.4269E+071.8633E+031.6415E+031.6425E+032.3723E+032.0319E+03
Avg2.6305E+082.5424E+032.5355E+032.6446E+032.9599E+033.8274E+03
Std3.3804E+084.0659E+027.4483E+026.2040E+026.9366E+023.7652E+03
Rank621345
F12Best1.4244E+051.7569E+032.0335E+032.3438E+032.1797E+032.5039E+03
Avg4.3495E+062.8663E+032.9544E+033.5312E+033.6218E+033.1982E+03
Std5.1856E+066.1828E+028.4343E+028.6897E+029.9961E+026.1612E+02
Rank612453
F13Best9.6618E+031.5030E+031.5357E+031.5073E+031.4920E+031.5603E+03
Avg2.0121E+051.6108E+031.5946E+031.6030E+031.6636E+031.6369E+03
Std4.8201E+058.3032E+015.8757E+016.9870E+017.5948E+015.1682E+01
Rank631254
F14Best2.5911E+041.6496E+031.5781E+031.6266E+031.6336E+031.5711E+03
Avg1.2174E+061.7182E+031.8883E+031.7263E+031.7574E+031.8400E+03
Std1.9415E+065.3115E+013.0372E+021.1643E+021.1380E+022.1117E+02
Rank615234
F15Best2.8693E+032.2821E+032.1648E+032.1815E+032.0428E+032.0428E+03
Avg3.4525E+032.7600E+032.6854E+032.6362E+032.6322E+032.6366E+03
Std3.6857E+022.9890E+023.7439E+022.9228E+023.1478E+023.1501E+02
Rank654213
F16Best2.1880E+031.8460E+031.7884E+031.7877E+031.7872E+031.7833E+03
Avg2.3653E+032.1876E+032.1556E+032.1624E+032.0865E+032.0799E+03
Std1.6112E+023.6427E+023.4803E+023.5899E+022.4206E+022.4010E+02
Rank653421
F17Best8.3824E+041.8749E+031.8352E+031.9304E+031.8740E+031.8847E+03
Avg8.5969E+051.9670E+031.9808E+031.9890E+031.9645E+032.8078E+03
Std1.1545E+067.8074E+011.0036E+026.0686E+017.7551E+011.3783E+03
Rank623415
F18Best1.0096E+042.0982E+032.0194E+032.1319E+032.0294E+032.1536E+03
Avg8.0005E+052.2583E+032.2231E+032.3355E+032.2744E+033.2714E+03
Std1.5036E+061.1587E+021.4100E+022.1651E+022.2885E+021.7664E+03
Rank621435
F19Best2.4491E+032.3036E+032.3046E+032.4117E+032.3846E+032.4027E+03
Avg2.6652E+032.5553E+032.5454E+032.5620E+032.5587E+032.5562E+03
Std1.7671E+021.4506E+021.2500E+021.0097E+021.0561E+029.6848E+01
Rank621543
F20Best2.4608E+032.3552E+032.3552E+032.3424E+032.3459E+032.3444E+03
Avg2.5290E+032.4273E+032.4197E+032.4149E+032.4159E+032.4155E+03
Std4.7807E+015.3818E+014.8297E+014.9075E+014.7729E+014.8298E+01
Rank654132
F21Best2.5992E+032.3000E+032.3000E+032.3000E+032.3000E+032.3000E+03
Avg5.5979E+035.1563E+035.2025E+035.2412E+035.1948E+035.1970E+03
Std2.6890E+032.5159E+032.5502E+032.5864E+032.5404E+032.5433E+03
Rank614523
F22Best2.8342E+032.7769E+032.7669E+032.7771E+032.7771E+032.7771E+03
Avg2.9360E+032.8413E+032.8270E+032.8285E+032.8223E+032.8221E+03
Std6.8458E+014.2575E+014.2612E+013.8588E+014.1651E+014.1427E+01
Rank653421
F23Best2.9924E+032.9348E+032.9260E+032.9147E+032.9123E+032.9109E+03
Avg3.0454E+033.0422E+033.0241E+033.0179E+033.0077E+033.0060E+03
Std3.9001E+016.2653E+016.4212E+016.5875E+015.9665E+016.0296E+01
Rank654321
F24Best3.0607E+032.8752E+032.8753E+032.8752E+032.8752E+032.8751E+03
Avg3.2809E+032.8780E+032.8778E+032.8785E+032.8778E+032.8867E+03
Std1.3704E+023.8366E+002.8270E+003.1429E+002.9136E+001.9711E+01
Rank631425
F25Best4.7183E+032.8000E+032.8000E+032.8000E+032.8000E+032.8000E+03
Avg6.4322E+035.0041E+035.0160E+035.0279E+035.0357E+035.0439E+03
Std8.4653E+028.2847E+028.7033E+028.6496E+028.7242E+028.7179E+02
Rank612345
F26Best3.2573E+033.2000E+033.2000E+033.1685E+033.1644E+033.1652E+03
Avg3.3100E+033.2000E+033.2000E+033.1969E+033.1932E+033.1935E+03
Std3.0583E+018.3370E-051.2162E-049.9486E+001.4287E+011.3797E+01
Rank654312
F27Best3.7060E+033.1000E+033.1000E+033.1000E+033.1000E+033.1000E+03
Avg3.9841E+033.1964E+033.1813E+033.1207E+033.1303E+033.1309E+03
Std2.2522E+028.9891E+017.5969E+014.3549E+016.7882E+016.8614E+01
Rank654123
F28Best4.0254E+033.7613E+033.8203E+033.7581E+033.7938E+033.8035E+03
Avg4.6093E+034.2202E+034.1344E+034.0753E+034.0308E+034.0468E+03
Std3.0880E+022.4769E+022.6737E+022.7452E+022.1534E+022.0096E+02
Rank654312
F29Best1.8822E+063.3487E+033.5009E+033.4737E+033.5120E+033.4586E+03
Avg2.0801E+073.5896E+033.7655E+033.9714E+035.0017E+033.8130E+03
Std2.2612E+071.6874E+024.2749E+028.5721E+023.4195E+033.5703E+02
Rank612453
Table A7. Experiments comparing EECO with different parameter a s (50D).
Table A7. Experiments comparing EECO with different parameter a s (50D).
No.IndexECOa = 0.5a = 0.6a = 0.7a = 0.8a = 0.9
F1Best1.3982E+101.0000E+021.0000E+021.0000E+021.0000E+021.0000E+02
Avg2.7507E+101.0143E+021.0000E+021.0000E+021.0000E+021.0000E+02
Std1.2295E+103.3546E+003.5315E-041.1651E-064.1379E-068.7994E-06
Rank654123
F2Best6.4697E+043.0000E+023.0000E+023.0000E+023.0000E+023.0000E+02
Avg1.0822E+053.0000E+023.0000E+023.0000E+023.0000E+023.0000E+02
Std3.8466E+042.6790E-052.2644E-052.4328E-052.4194E-053.3586E-03
Rank621345
F3Best2.2968E+034.0000E+024.0000E+024.0000E+024.0000E+024.0000E+02
Avg4.6065E+034.0120E+024.0040E+024.0120E+024.0120E+024.0177E+02
Std2.4371E+031.9257E+001.2607E+001.9257E+001.9257E+001.9810E+00
Rank621435
F4Best8.5796E+027.4277E+027.2287E+027.4078E+027.3779E+027.3083E+02
Avg9.9192E+028.0356E+027.9759E+027.9600E+027.9550E+027.9351E+02
Std9.4684E+014.3602E+015.1335E+014.5307E+014.4688E+014.7362E+01
Rank654321
F5Best6.5862E+026.4217E+026.4148E+026.4148E+026.4132E+026.4074E+02
Avg6.6684E+026.5081E+026.5000E+026.5021E+026.4969E+026.4974E+02
Std5.5643E+005.1802E+005.5751E+005.6253E+005.8729E+005.7551E+00
Rank653412
F6Best1.4736E+031.0846E+031.0827E+031.0745E+031.0835E+031.0835E+03
Avg1.5961E+031.3883E+031.3649E+031.3545E+031.3414E+031.3453E+03
Std7.0588E+011.6236E+021.4387E+021.4172E+021.3758E+021.3872E+02
Rank654312
F7Best1.2522E+031.0189E+031.0179E+031.0179E+031.0179E+031.0149E+03
Avg1.3018E+031.0951E+031.0945E+031.0928E+031.0900E+031.0890E+03
Std4.1265E+015.1674E+015.2721E+015.0550E+014.9384E+015.0054E+01
Rank654321
F8Best1.7076E+046.1237E+036.2360E+036.2498E+036.2687E+036.2408E+03
Avg2.3943E+049.2604E+039.1744E+039.1777E+038.8459E+038.8528E+03
Std4.7473E+031.7466E+031.7814E+031.7938E+031.9677E+031.9827E+03
Rank653412
F9Best9.4499E+036.7913E+036.6107E+036.2585E+036.6329E+036.2913E+03
Avg1.2865E+048.2946E+038.2973E+038.2658E+038.1524E+038.0868E+03
Std1.4205E+037.3038E+029.3217E+021.0069E+039.0067E+029.7949E+02
Rank645321
F10Best2.6975E+031.1915E+031.2005E+031.2075E+031.2293E+031.2383E+03
Avg7.5828E+031.2857E+031.2942E+031.2936E+031.3034E+031.3032E+03
Std4.1000E+035.8890E+016.5701E+016.4788E+014.8903E+015.4899E+01
Rank613254
F11Best9.4040E+082.6603E+033.4740E+033.7836E+032.7355E+033.2915E+03
Avg3.1306E+094.5399E+034.5065E+035.0763E+036.4612E+038.1929E+03
Std1.6180E+091.0631E+038.1147E+027.7520E+026.1899E+037.0498E+03
Rank621345
F12Best3.0077E+072.7646E+032.3687E+032.6882E+032.4087E+032.7124E+03
Avg2.9633E+083.8901E+033.4318E+034.4038E+033.8809E+035.7969E+03
Std3.3853E+087.9627E+027.1599E+022.0553E+031.0482E+033.8287E+03
Rank631425
F13Best3.4667E+041.6472E+031.6149E+031.6205E+031.6794E+031.5158E+03
Avg7.6567E+051.7621E+031.7951E+031.7619E+031.8328E+032.2929E+03
Std9.8799E+051.1382E+021.2679E+021.0739E+021.1478E+028.5012E+02
Rank623145
F14Best7.2450E+051.7850E+031.6544E+031.7091E+031.6747E+031.9018E+03
Avg4.9169E+071.9577E+032.0519E+032.0958E+032.2319E+032.6003E+03
Std8.5723E+071.9572E+024.8844E+024.7568E+024.1193E+021.1742E+03
Rank612345
F15Best3.6363E+032.6617E+032.6616E+032.6616E+032.6617E+032.6616E+03
Avg4.4666E+033.6028E+033.5435E+033.4762E+033.4990E+033.5221E+03
Std6.9770E+025.3232E+025.7077E+025.7146E+025.7047E+025.6806E+02
Rank654123
F16Best3.3004E+033.0542E+033.0266E+033.0247E+033.0066E+033.0525E+03
Avg3.9210E+033.4643E+033.4666E+033.4245E+033.4492E+033.4575E+03
Std5.2555E+022.8083E+022.8539E+022.2888E+022.6341E+022.4386E+02
Rank645123
F17Best4.7151E+051.8750E+031.9655E+031.8931E+031.8912E+033.2855E+03
Avg6.7951E+062.0366E+032.0383E+031.9959E+032.3766E+036.9861E+03
Std6.2519E+061.3461E+025.3906E+017.2524E+013.9751E+023.9086E+03
Rank623145
F18Best2.8826E+052.0910E+032.0533E+032.2315E+032.3956E+032.3188E+03
Avg2.3034E+072.3706E+032.4029E+032.7873E+033.6576E+038.0225E+03
Std5.1801E+072.7348E+022.6305E+026.1208E+021.6342E+035.9731E+03
Rank612345
F19Best3.0192E+032.5548E+032.5459E+032.5669E+032.5479E+032.5469E+03
Avg3.5627E+033.1917E+033.1320E+033.1304E+033.1251E+033.1297E+03
Std3.1123E+024.2055E+024.0493E+024.2369E+024.2248E+024.1809E+02
Rank654312
F20Best2.6066E+032.4536E+032.4540E+032.4566E+032.4566E+032.4585E+03
Avg2.7480E+032.5709E+032.5729E+032.5726E+032.5715E+032.5716E+03
Std9.5071E+016.2980E+016.3498E+016.2273E+016.3547E+016.2944E+01
Rank615423
F21Best1.3152E+048.3074E+038.1761E+038.3607E+038.3586E+038.1970E+03
Avg1.4535E+049.4961E+039.4112E+039.3560E+039.4815E+039.6024E+03
Std8.9691E+027.6530E+027.4955E+026.5483E+028.0954E+028.7011E+02
Rank642135
F22Best3.3001E+033.0622E+033.0162E+033.0471E+033.0050E+033.0087E+03
Avg3.3894E+033.1991E+033.1847E+033.1749E+033.1461E+033.1415E+03
Std8.4934E+011.0798E+021.1520E+021.1480E+021.2839E+021.3008E+02
Rank654321
F23Best3.4416E+033.1810E+033.1482E+033.1462E+033.0585E+033.0920E+03
Avg3.5253E+033.3530E+033.2986E+033.2880E+033.2715E+033.2577E+03
Std7.0905E+011.2242E+021.2132E+021.2895E+021.4544E+021.4702E+02
Rank654321
F24Best4.5928E+032.9312E+032.9313E+032.9313E+032.9313E+032.9313E+03
Avg6.1549E+032.9656E+032.9703E+032.9766E+032.9557E+032.9596E+03
Std1.1810E+033.1874E+011.9223E+013.0393E+012.8872E+011.9907E+01
Rank634512
F25Best9.3476E+032.9000E+032.9000E+032.9000E+032.9000E+032.9000E+03
Avg1.1153E+048.0455E+038.2574E+038.1936E+037.7180E+037.9819E+03
Std1.2482E+032.0987E+032.1142E+032.1338E+032.6686E+032.2444E+03
Rank635412
F26Best3.5181E+033.2000E+033.2000E+033.2000E+033.2000E+033.2000E+03
Avg3.8122E+033.2000E+033.2000E+033.2000E+033.2171E+033.2000E+03
Std2.4505E+021.5786E-042.4357E-041.6338E-045.4060E+011.2729E-04
Rank621354
F27Best5.2264E+033.3000E+033.3000E+033.3000E+033.3000E+033.3000E+03
Avg6.7929E+033.3000E+033.3000E+033.3000E+033.3000E+033.3000E+03
Std1.5797E+033.2608E-044.0006E-043.2784E-042.5321E-042.7928E-04
Rank615342
F28Best5.3623E+034.1821E+034.3256E+034.1128E+034.0205E+033.9143E+03
Avg6.6733E+034.7937E+034.7995E+034.7584E+034.6540E+034.6277E+03
Std8.6922E+023.3154E+023.0021E+023.5240E+023.6891E+024.5449E+02
Rank645321
F29Best6.0193E+073.7396E+033.8566E+033.6930E+033.4871E+033.9225E+03
Avg1.8378E+085.7981E+036.9528E+034.6114E+034.6278E+038.5123E+03
Std1.7870E+084.4484E+034.8510E+031.0670E+031.0772E+036.5112E+03
Rank634125
Table A8. Experiments comparing EECO with different parameter a s (100D).
Table A8. Experiments comparing EECO with different parameter a s (100D).
No.IndexECOa = 0.5a = 0.6a = 0.7a = 0.8a = 0.9
F1Best1.0516E+112.7355E+032.0362E+032.0566E+031.2195E+021.9212E+02
Avg1.1103E+119.8305E+037.2179E+038.1565E+039.1249E+038.7906E+03
Std4.9348E+094.8534E+033.9671E+034.6948E+038.5787E+039.8954E+03
Rank651243
F2Best2.5917E+053.9492E+045.1115E+043.1963E+043.7096E+044.9098E+04
Avg2.8050E+055.7541E+045.4596E+045.0453E+045.7097E+046.0791E+04
Std2.5113E+043.0564E+042.8414E+031.6305E+041.7974E+041.2574E+04
Rank642135
F3Best1.1491E+045.8216E+025.6703E+025.7384E+025.7172E+025.7646E+02
Avg1.6719E+046.0899E+025.9268E+026.0577E+026.0567E+026.2239E+02
Std8.1866E+032.7027E+013.5782E+013.3935E+013.5256E+013.0835E+01
Rank641325
F4Best1.5748E+031.1686E+031.1626E+031.1746E+031.1666E+031.1696E+03
Avg1.6415E+031.2064E+031.2069E+031.2134E+031.2034E+031.2044E+03
Std4.5651E+014.0152E+014.8535E+014.5135E+014.4628E+014.3754E+01
Rank634512
F5Best6.7534E+026.5439E+026.5321E+026.5284E+026.5310E+026.5332E+02
Avg6.7727E+026.5835E+026.5808E+026.5779E+026.5799E+026.5814E+02
Std1.9568E+004.6156E+005.1737E+005.7479E+005.6611E+005.4908E+00
Rank653124
F6Best3.1609E+032.5121E+032.4678E+032.5250E+032.4412E+032.4539E+03
Avg3.2687E+032.7763E+032.7505E+032.7037E+032.6838E+032.6903E+03
Std1.3907E+022.2560E+022.4892E+021.8362E+022.1687E+022.0897E+02
Rank654312
F7Best1.8844E+031.4955E+031.5074E+031.5074E+031.5134E+031.5114E+03
Avg2.0902E+031.5517E+031.5402E+031.5502E+031.5502E+031.5502E+03
Std1.5760E+025.5990E+014.6310E+014.3130E+014.4397E+014.9924E+01
Rank651342
F8Best4.8102E+041.6571E+041.6601E+041.6599E+041.6582E+041.6612E+04
Avg5.6594E+041.9584E+042.1672E+042.1686E+041.9625E+041.9724E+04
Std6.9367E+032.0606E+035.3329E+035.3668E+032.0735E+032.1294E+03
Rank614523
F9Best2.5800E+041.5260E+041.5136E+041.5334E+041.5201E+041.5195E+04
Avg2.7131E+041.6361E+041.5928E+041.6271E+041.6417E+041.6592E+04
Std1.5785E+031.1549E+038.6530E+028.8180E+021.1921E+031.3406E+03
Rank631245
F10Best5.0265E+042.2440E+032.2198E+032.1987E+032.1024E+032.1668E+03
Avg8.1274E+042.2856E+032.2876E+032.3552E+032.3643E+032.3560E+03
Std3.9368E+045.4685E+019.2419E+011.7630E+023.5223E+021.8517E+02
Rank612354
F11Best1.9040E+106.1180E+056.0306E+056.6267E+053.7465E+056.2566E+05
Avg2.7304E+101.0551E+069.0999E+058.1703E+059.2509E+051.0787E+06
Std6.5837E+093.3217E+053.0758E+052.0875E+055.4639E+057.6097E+05
Rank642135
F12Best4.4658E+086.6312E+036.4242E+036.6649E+036.4993E+036.7171E+03
Avg1.7600E+098.8200E+038.7041E+038.6476E+038.4896E+038.5395E+03
Std1.0977E+093.1820E+033.2192E+033.1393E+032.9186E+033.0369E+03
Rank654312
F13Best2.4685E+062.5915E+042.7599E+043.4168E+042.7228E+042.4253E+04
Avg9.9605E+063.9322E+044.3286E+044.4772E+044.3829E+043.9653E+04
Std1.1653E+072.3415E+041.7869E+041.3445E+041.7946E+041.1935E+04
Rank613542
F14Best8.5045E+072.5813E+032.3992E+032.2810E+032.4414E+032.3055E+03
Avg1.4398E+081.1474E+041.2266E+041.2489E+041.2269E+041.2220E+04
Std6.2725E+071.3058E+041.5074E+041.5458E+041.5243E+041.5061E+04
Rank613542
F15Best8.9502E+035.0165E+034.9661E+035.0544E+035.0358E+034.9132E+03
Avg9.3818E+035.4519E+035.4298E+035.4858E+035.4801E+035.4861E+03
Std4.4861E+024.2214E+023.9786E+024.4746E+023.9855E+024.4726E+02
Rank621435
F16Best6.3541E+035.3851E+035.3515E+035.5186E+035.3938E+035.5299E+03
Avg8.3109E+036.3625E+036.2110E+036.7242E+036.3913E+036.4490E+03
Std2.3441E+037.6691E+027.6225E+021.0471E+037.5598E+026.9518E+02
Rank621534
F17Best1.8859E+063.5457E+041.7800E+044.4354E+044.2100E+043.9002E+04
Avg7.1368E+065.4331E+045.5221E+047.1847E+045.1266E+046.4633E+04
Std4.2842E+062.0149E+042.7475E+042.8583E+041.0155E+041.8453E+04
Rank623514
F18Best1.6028E+083.9116E+033.2475E+033.2101E+033.1791E+032.8712E+03
Avg4.5686E+086.8990E+036.5667E+036.8000E+036.6747E+035.9845E+03
Std3.6604E+085.3093E+036.1591E+035.9971E+035.4749E+035.5463E+03
Rank652431
F19Best4.7506E+034.5373E+034.5213E+034.5196E+034.5386E+034.5325E+03
Avg5.9860E+035.0542E+034.9895E+035.0466E+035.0555E+034.9888E+03
Std8.9336E+026.2926E+025.3692E+025.9563E+025.9846E+025.8615E+02
Rank642351
F20Best3.5372E+033.0067E+032.9870E+032.9957E+033.0169E+032.9867E+03
Avg3.6555E+033.1283E+033.1281E+033.1226E+033.1317E+033.1161E+03
Std9.5124E+018.2571E+019.5133E+018.8523E+017.6772E+018.8214E+01
Rank643251
F21Best2.8975E+041.7786E+041.8288E+041.7665E+041.7295E+041.6959E+04
Avg3.0308E+041.9765E+041.9873E+041.9803E+041.9320E+041.9476E+04
Std1.1579E+031.6795E+031.5984E+031.8522E+031.6695E+032.0595E+03
Rank635412
F22Best4.0146E+033.8719E+033.8307E+033.8316E+033.8335E+033.8422E+03
Avg4.4003E+034.0090E+033.9492E+033.9820E+033.9667E+033.9331E+03
Std2.7683E+021.4931E+021.3990E+021.6874E+021.7394E+021.3387E+02
Rank652431
F23Best4.8007E+034.4830E+034.3510E+034.4365E+034.3493E+034.3611E+03
Avg5.1692E+035.0090E+034.7597E+034.7822E+034.7365E+034.6987E+03
Std2.7420E+024.6767E+023.1209E+023.6610E+023.8043E+023.7742E+02
Rank653421
F24Best9.5292E+033.1168E+033.0618E+033.2057E+033.1789E+033.1984E+03
Avg1.1884E+043.2610E+033.2253E+033.2862E+033.2670E+033.2563E+03
Std2.4724E+031.2330E+021.2207E+028.8634E+011.0082E+024.3313E+01
Rank631542
F25Best2.0470E+041.4903E+041.4342E+041.4437E+041.4539E+041.4504E+04
Avg2.5238E+042.0051E+042.0261E+042.0388E+042.0108E+042.0188E+04
Std3.9562E+034.6741E+035.3808E+035.5320E+035.2042E+035.3760E+03
Rank614523
F26Best4.0171E+033.2000E+033.2000E+033.2000E+033.2000E+033.3814E+03
Avg4.4848E+033.7430E+033.3981E+033.4600E+033.6156E+033.7416E+03
Std6.6520E+026.4311E+023.9622E+023.0224E+024.9520E+023.2470E+02
Rank651234
F27Best1.0026E+043.2951E+033.2951E+033.2951E+033.3164E+033.3173E+03
Avg1.7443E+043.2990E+033.3028E+033.3297E+033.3379E+033.3287E+03
Std5.0251E+036.5512E+001.4984E+012.6586E+012.0147E+019.3743E+00
Rank612453
F28Best1.2195E+046.3031E+036.2190E+036.2987E+035.9239E+035.6597E+03
Avg1.4170E+047.2658E+037.0021E+037.0854E+036.8564E+036.9274E+03
Std2.8708E+039.0276E+026.3775E+029.4837E+021.1374E+031.1567E+03
Rank653412
F29Best5.5469E+084.3864E+034.6825E+034.7552E+035.5174E+035.0398E+03
Avg7.5685E+087.8931E+038.1504E+038.0196E+038.7649E+038.5681E+03
Std1.6456E+084.4293E+034.9147E+035.7282E+035.7765E+035.7726E+03
Rank613254
Table A9. Experiments comparing EECO with different strategies (10D).
Table A9. Experiments comparing EECO with different strategies (10D).
No.IndexECOECO-RECO-PECO-TECO-RPECO-RTECO-PTEECO
F1Best6.3568E+063.4081E+029.4699E+026.6813E+041.0000E+021.0000E+021.0000E+021.0000E+02
Avg1.5632E+088.6949E+041.7517E+044.1678E+065.7070E+021.0000E+021.0019E+021.0000E+02
Std3.1359E+082.0888E+054.2886E+046.2632E+061.3967E+032.1836E-077.2283E-010.0000E+00
Rank86574231
F2Best7.2490E+023.0000E+023.0001E+023.7683E+023.0000E+023.0000E+023.0000E+023.0000E+02
Avg3.1268E+033.0342E+023.0347E+021.0111E+033.0000E+023.0000E+023.0000E+023.0000E+02
Std2.1573E+031.0140E+011.0456E+015.8115E+029.0236E-067.4740E-129.9336E-110.0000E+00
Rank85674231
F3Best4.0663E+024.0270E+024.0346E+024.0175E+024.0000E+024.0000E+024.0000E+024.0000E+02
Avg4.2652E+024.0478E+024.0503E+024.0841E+024.0300E+024.0000E+024.0000E+024.0000E+02
Std2.3682E+011.2658E+009.7697E-017.0677E+001.4796E+001.2855E-121.7717E-134.1355E-13
Rank85674311
F4Best5.1504E+025.0873E+025.1582E+025.1087E+025.0106E+025.0696E+025.0995E+025.0199E+02
Avg5.4079E+025.1957E+025.2575E+025.2398E+025.0561E+025.2912E+025.2136E+025.0451E+02
Std1.4548E+018.1612E+005.6800E+007.1122E+003.2460E+001.8853E+017.4253E+001.7983E+00
Rank83652741
F5Best6.0731E+026.0007E+026.0018E+026.0852E+026.0000E+026.0516E+026.0720E+026.0000E+02
Avg6.2141E+026.0133E+026.0043E+026.1743E+026.0003E+026.1352E+026.1785E+026.0001E+02
Std9.6906E+003.4964E+003.6358E-018.0170E+007.1318E-025.9790E+007.3533E+003.7882E-02
Rank84362571
F6Best7.2950E+027.1901E+027.2143E+027.3110E+027.1208E+027.1789E+027.2024E+027.1089E+02
Avg7.6287E+027.3210E+027.3799E+027.5131E+027.1841E+027.4524E+027.4477E+027.1422E+02
Std1.8573E+017.9956E+007.6167E+001.3791E+015.0688E+001.3200E+011.3906E+013.3408E+00
Rank83472651
F7Best8.1459E+028.1186E+028.1230E+028.1247E+028.0100E+028.0995E+028.0995E+028.0199E+02
Avg8.3687E+028.2398E+028.2517E+028.2672E+028.0576E+028.2235E+028.2341E+028.0829E+02
Std9.3431E+008.1097E+005.5161E+008.4988E+003.8371E+009.1874E+009.6601E+004.8839E+00
Rank85671342
F8Best9.2354E+029.0001E+029.0000E+029.2033E+029.0000E+029.1734E+029.2501E+029.0000E+02
Avg1.0787E+039.0008E+029.0073E+021.0804E+039.0000E+021.0789E+031.0750E+039.0000E+02
Std1.2133E+021.2950E-011.8366E+001.4999E+024.7727E-081.4738E+021.3488E+020.0000E+00
Rank63482751
F9Best1.6251E+031.9746E+031.7746E+031.5390E+031.1735E+031.2540E+031.4894E+031.3769E+03
Avg2.0675E+032.2216E+032.2668E+032.0639E+032.0169E+031.7952E+031.9113E+031.6773E+03
Std3.3508E+022.1401E+022.8930E+022.4145E+023.4517E+022.6213E+021.7724E+021.9887E+02
Rank67854231
F10Best1.1602E+031.1055E+031.1035E+031.1269E+031.1008E+031.1209E+031.1249E+031.1010E+03
Avg1.2608E+031.1149E+031.1155E+031.1905E+031.1074E+031.1761E+031.1517E+031.1069E+03
Std9.8558E+019.8691E+001.2798E+011.1368E+024.5889E+004.5928E+013.4474E+016.5809E+00
Rank83472651
F11Best9.6759E+041.5531E+031.5929E+037.8112E+031.3209E+031.3186E+031.3186E+031.3186E+03
Avg4.9010E+066.5012E+034.5646E+055.2419E+052.7239E+052.1391E+031.5788E+031.5028E+03
Std6.3820E+061.0932E+041.7416E+066.3214E+051.0482E+061.5224E+031.9574E+022.0539E+02
Rank84675321
F12Best1.9964E+031.3197E+031.3372E+031.9635E+031.3068E+031.4370E+031.3984E+031.3054E+03
Avg1.5972E+041.4547E+031.5285E+035.1567E+031.4662E+031.8507E+031.8035E+031.4125E+03
Std1.8296E+041.2786E+022.2942E+023.9474E+031.4450E+023.1223E+023.3130E+021.3790E+02
Rank82473651
F13Best1.4708E+031.4134E+031.4164E+031.4568E+031.4031E+031.4341E+031.4255E+031.4010E+03
Avg1.5422E+031.4266E+031.4281E+031.4852E+031.4174E+031.4893E+031.4674E+031.4181E+03
Std8.5245E+014.7795E+006.9769E+002.4760E+019.8792E+003.9156E+013.0306E+011.2380E+01
Rank83461752
F14Best1.6616E+031.5029E+031.5032E+031.6092E+031.5010E+031.5035E+031.5111E+031.5012E+03
Avg2.5911E+031.5243E+031.5204E+031.8519E+031.5188E+031.6003E+031.5924E+031.5070E+03
Std1.0180E+032.2785E+011.8269E+012.4737E+021.8296E+016.0997E+017.2889E+017.3589E+00
Rank84372651
F15Best1.6103E+031.6081E+031.6176E+031.6546E+031.6018E+031.6014E+031.6033E+031.6006E+03
Avg1.7834E+031.6557E+031.6565E+031.7715E+031.6153E+031.6999E+031.7159E+031.6043E+03
Std1.0502E+023.6519E+013.1351E+019.2316E+013.3264E+018.5837E+011.0326E+025.0260E+00
Rank83472561
F16Best1.7553E+031.7360E+031.7485E+031.7457E+031.7302E+031.7308E+031.7312E+031.7017E+03
Avg1.7989E+031.7768E+031.7701E+031.7671E+031.7400E+031.7631E+031.7566E+031.7299E+03
Std4.2116E+012.2765E+011.4271E+011.4216E+011.0717E+013.0365E+011.3362E+011.9279E+01
Rank87652431
F17Best2.8667E+031.8246E+031.8271E+032.5924E+031.8212E+031.8265E+031.8252E+031.8020E+03
Avg2.0116E+041.9457E+031.8840E+031.9664E+041.8541E+031.8945E+031.9137E+031.8248E+03
Std1.5720E+042.5294E+028.6589E+011.2765E+047.5336E+017.5361E+018.0518E+011.3687E+01
Rank86372451
F18Best1.9546E+031.9045E+031.9040E+031.9420E+031.9006E+031.9150E+031.9090E+031.9001E+03
Avg3.0823E+031.9068E+031.9061E+032.1495E+031.9032E+031.9786E+031.9722E+031.9023E+03
Std1.8128E+032.4554E+002.0609E+002.5198E+022.2375E+004.0846E+014.6082E+011.4866E+00
Rank84372651
F19Best2.0621E+032.0468E+032.0591E+032.0313E+032.0210E+032.0390E+032.0316E+032.0003E+03
Avg2.1270E+032.0950E+032.0955E+032.1223E+032.0391E+032.0841E+032.1185E+032.0217E+03
Std4.6113E+013.6929E+013.5544E+015.8736E+011.5298E+013.6869E+015.7480E+011.2913E+01
Rank84572361
F20Best2.2086E+032.2036E+032.2066E+032.2028E+032.2000E+032.2024E+032.2022E+032.2000E+03
Avg2.2536E+032.2950E+032.2943E+032.2578E+032.2782E+032.2599E+032.2468E+032.2711E+03
Std5.2251E+014.6092E+014.1245E+016.1546E+014.7641E+016.3311E+016.4381E+015.0488E+01
Rank28736415
F21Best2.2577E+032.2118E+032.2121E+032.2469E+032.2116E+032.2116E+032.2457E+032.2000E+03
Avg2.3184E+032.2907E+032.2846E+032.3068E+032.2882E+032.2966E+032.3037E+032.2882E+03
Std2.8828E+013.2387E+013.3724E+011.7493E+013.1126E+013.6065E+011.7765E+013.1550E+01
Rank84172563
F22Best2.6198E+032.6031E+032.6074E+032.6139E+032.6000E+032.6115E+032.6098E+032.6043E+03
Avg2.6346E+032.6188E+032.6225E+032.6262E+032.6104E+032.6239E+032.6200E+032.6083E+03
Std1.9097E+018.1275E+001.2546E+019.3875E+006.1417E+009.8880E+006.8405E+002.7440E+00
Rank83572641
F23Best2.5475E+032.6093E+032.6808E+032.5317E+032.5000E+032.5000E+032.5000E+032.5000E+03
Avg2.7375E+032.7361E+032.7449E+032.7127E+032.7120E+032.7204E+032.7009E+032.7058E+03
Std6.7204E+013.5875E+011.8709E+018.4827E+016.9021E+019.1787E+011.0415E+028.3745E+01
Rank76843512
F24Best2.9133E+032.8977E+032.8977E+032.8990E+032.8981E+032.8978E+032.8981E+032.8977E+03
Avg2.9530E+032.9247E+032.9286E+032.9479E+032.9487E+032.9363E+032.9407E+032.9366E+03
Std2.3641E+013.4790E+013.5185E+014.4075E+013.4622E+012.3095E+014.2636E+012.9542E+01
Rank81267354
F25Best2.9206E+032.9002E+032.9002E+032.9055E+032.8000E+032.6000E+032.8000E+032.9000E+03
Avg3.1026E+032.9436E+032.9230E+033.0276E+032.9265E+033.0110E+033.0082E+032.9230E+03
Std1.0755E+025.2072E+013.9557E+018.5862E+016.6434E+011.8356E+021.0894E+025.3723E+01
Rank84173652
F26Best3.0914E+033.0891E+033.0894E+033.0900E+033.0893E+033.0884E+033.0765E+033.0884E+03
Avg3.1013E+033.0927E+033.0991E+033.0950E+033.1013E+033.0945E+033.0911E+033.0959E+03
Std1.1701E+013.5382E+001.6515E+013.6588E+001.8993E+014.9097E+006.5488E+001.0550E+01
Rank72648315
F27Best3.1801E+033.1647E+033.1687E+033.1968E+033.2087E+033.1000E+033.1000E+033.1000E+03
Avg3.4163E+033.3593E+033.3706E+033.4279E+033.4421E+033.2530E+033.2478E+033.2558E+03
Std1.3588E+028.5758E+019.8072E+011.4533E+021.3197E+025.4080E+015.5797E+014.7561E+01
Rank64578213
F28Best3.1753E+033.1573E+033.1556E+033.1696E+033.1415E+033.1488E+033.1615E+033.1285E+03
Avg3.2381E+033.2076E+033.2025E+033.2541E+033.1693E+033.2309E+033.2427E+033.1616E+03
Std4.2469E+013.7233E+013.2331E+016.4757E+013.4182E+017.1347E+016.2455E+014.3286E+01
Rank64382571
F29Best1.9416E+043.6599E+033.7610E+037.4945E+033.5050E+033.2322E+033.2439E+033.2239E+03
Avg8.0401E+054.8655E+056.3152E+058.5133E+053.2142E+053.4133E+033.4298E+033.4510E+03
Std7.4313E+057.3926E+051.0372E+068.1339E+054.7485E+051.3867E+028.6260E+014.7789E+02
Rank75684123
Table A10. Experiments comparing EECO with different strategies (30D).
Table A10. Experiments comparing EECO with different strategies (30D).
No.IndexECOECO-RECO-PECO-TECO-RPECO-RTECO-PTEECO
F1Best1.5106E+091.2621E+072.8527E+071.9648E+084.3121E+051.0000E+021.0000E+021.0000E+02
Avg7.7062E+091.4281E+091.0271E+091.5388E+092.5736E+071.0003E+021.0000E+021.0000E+02
Std3.5527E+092.7110E+091.7790E+091.1116E+092.2270E+071.1957E-014.0902E-075.3627E-10
Rank86574321
F2Best3.1205E+048.7174E+021.9051E+031.2223E+041.0580E+033.0000E+023.0000E+023.0000E+02
Avg5.2052E+044.1547E+036.8564E+032.9623E+043.6491E+033.0000E+023.0000E+023.0000E+02
Std1.2534E+042.9907E+034.0857E+039.6754E+032.1574E+032.5582E-063.3100E-066.9834E-13
Rank85674231
F3Best7.6180E+025.1010E+024.9059E+025.6375E+024.8396E+024.0000E+024.0000E+024.0000E+02
Avg1.1569E+035.7615E+026.0134E+026.1614E+025.1568E+024.0292E+024.0186E+024.0186E+02
Std3.0717E+021.1645E+021.6387E+023.4472E+012.0865E+011.8248E+002.0587E+002.0587E+00
Rank85674321
F4Best6.5226E+025.7103E+026.4876E+026.1010E+025.3872E+025.6865E+025.9751E+025.1990E+02
Avg7.4363E+026.6984E+026.8004E+026.9766E+025.9287E+026.4029E+026.6788E+025.4245E+02
Std4.8611E+012.9971E+011.9930E+014.1417E+014.0202E+014.6932E+013.6561E+012.4699E+01
Rank85672341
F5Best6.2982E+026.0400E+026.0684E+026.3117E+026.0169E+026.2765E+026.2896E+026.0122E+02
Avg6.4819E+026.1194E+026.1264E+026.4854E+026.0472E+026.4103E+026.4104E+026.0340E+02
Std9.6799E+005.1610E+005.4919E+001.0872E+012.9547E+008.7933E+008.3689E+001.7467E+00
Rank73482561
F6Best9.4885E+028.6284E+028.8462E+029.3392E+028.0285E+028.7394E+028.7878E+027.4415E+02
Avg1.1363E+039.2356E+029.2254E+021.0385E+038.6304E+029.6458E+029.7754E+027.6706E+02
Std1.0150E+023.9180E+012.8961E+017.8808E+012.6589E+016.7735E+017.4369E+011.6126E+01
Rank84372561
F7Best9.6946E+029.3324E+029.3928E+029.0278E+028.2132E+029.0745E+028.7263E+028.1094E+02
Avg1.0281E+039.8026E+029.8227E+029.6252E+028.9738E+029.5535E+029.3193E+028.2633E+02
Std3.4838E+012.8684E+012.3951E+013.5315E+013.5235E+013.2893E+013.4829E+011.0768E+01
Rank86752431
F8Best3.7868E+039.5982E+029.7128E+023.1158E+039.1764E+022.2491E+032.3138E+039.0235E+02
Avg6.6297E+031.4558E+031.2863E+035.1900E+031.1957E+033.6962E+033.6514E+031.0753E+03
Std1.7678E+035.5181E+022.7043E+021.8027E+032.9774E+021.2067E+039.4916E+022.6070E+02
Rank84372651
F9Best6.5418E+036.3440E+037.0759E+035.4871E+034.8488E+034.0567E+034.0790E+034.0675E+03
Avg7.4701E+037.4236E+038.0889E+036.7432E+037.2895E+034.8989E+035.1966E+035.0357E+03
Std5.0869E+026.1233E+025.5973E+027.8718E+029.3952E+025.1170E+025.9389E+025.9698E+02
Rank76845132
F10Best1.4005E+031.1892E+031.2037E+031.2586E+031.1220E+031.1667E+031.1438E+031.1318E+03
Avg2.4572E+031.2613E+031.2827E+031.4142E+031.1802E+031.2338E+031.2346E+031.1611E+03
Std6.0466E+025.5683E+011.0807E+021.0508E+023.7790E+014.8871E+016.0679E+012.1430E+01
Rank85672341
F11Best4.0632E+071.0030E+053.5878E+056.5983E+065.0402E+031.6490E+031.7116E+031.6653E+03
Avg3.7988E+083.7370E+077.7752E+062.7562E+072.8178E+052.5964E+034.9496E+032.3615E+03
Std2.9301E+089.4521E+071.5554E+073.0189E+074.7958E+057.3408E+026.0188E+034.0135E+02
Rank87564231
F12Best1.5773E+051.5525E+042.4240E+043.5489E+043.6691E+032.1581E+032.0606E+031.5151E+03
Avg3.9887E+064.5509E+045.4911E+041.3226E+051.1289E+043.6466E+033.3834E+032.2556E+03
Std7.3126E+062.5748E+042.0264E+049.5507E+047.9113E+031.1719E+037.8453E+026.0513E+02
Rank85674321
F13Best1.9405E+041.5170E+031.5180E+031.9972E+031.4547E+031.5167E+031.5089E+031.4290E+03
Avg2.0366E+051.5933E+031.5740E+031.7909E+041.4818E+031.6571E+031.6318E+031.4809E+03
Std1.8579E+051.3154E+023.4393E+013.3564E+042.4028E+018.9175E+016.7059E+013.7896E+01
Rank84372651
F14Best1.4059E+042.1148E+032.1998E+037.5684E+031.7285E+031.5716E+031.5804E+031.5598E+03
Avg4.2983E+055.0697E+038.8400E+036.8526E+042.1135E+031.8774E+031.7819E+031.6608E+03
Std1.2268E+062.9651E+038.6126E+035.7556E+043.5867E+023.6014E+021.5244E+024.9470E+01
Rank85674321
F15Best2.6898E+032.3336E+032.4629E+032.5848E+031.7160E+031.9750E+032.3100E+031.6027E+03
Avg3.1720E+032.7933E+032.9451E+033.0091E+032.0782E+032.5766E+032.7050E+031.8519E+03
Std2.9296E+022.7696E+022.8682E+022.7534E+022.7633E+022.9623E+022.9820E+022.1228E+02
Rank85672341
F16Best2.1910E+031.8304E+031.8650E+031.9721E+031.7834E+031.8629E+031.9335E+031.7361E+03
Avg2.4576E+032.0697E+032.1045E+032.2878E+031.8700E+032.1524E+032.2462E+031.8085E+03
Std2.2819E+021.5677E+021.8707E+022.3365E+021.1447E+021.8401E+022.3419E+027.7009E+01
Rank83472561
F17Best8.0686E+042.2224E+032.3376E+035.7372E+041.9583E+031.8886E+031.8660E+031.8689E+03
Avg1.2248E+065.6642E+035.4309E+031.3309E+052.1134E+032.0484E+037.1229E+031.9368E+03
Std1.0334E+065.2587E+033.2327E+037.6701E+041.4917E+021.3175E+029.2773E+035.3946E+01
Rank85473261
F18Best2.3623E+042.0776E+032.2630E+032.0819E+041.9433E+032.0542E+032.1738E+031.9224E+03
Avg9.8455E+062.7398E+033.7883E+032.8909E+052.0020E+032.2486E+036.0659E+031.9971E+03
Std2.9716E+071.2678E+031.7637E+033.9419E+054.2065E+011.7149E+029.5810E+035.4650E+01
Rank84572361
F19Best2.3612E+032.2060E+032.3893E+032.3155E+032.1107E+032.2834E+032.2706E+032.0256E+03
Avg2.6477E+032.5218E+032.6138E+032.5671E+032.2396E+032.5382E+032.5171E+032.0490E+03
Std1.6299E+022.0224E+021.2031E+021.6249E+021.5026E+021.5133E+021.7044E+021.6675E+01
Rank84762531
F20Best2.4608E+032.3833E+032.3928E+032.4110E+032.3267E+032.3459E+032.3816E+032.3131E+03
Avg2.5363E+032.4466E+032.4557E+032.4627E+032.3686E+032.4229E+032.4155E+032.3354E+03
Std4.4288E+013.4518E+012.8925E+014.1230E+013.2884E+014.0401E+013.4676E+012.8757E+01
Rank85672431
F21Best2.9319E+032.4166E+032.4519E+032.4245E+032.3151E+032.3000E+032.3000E+032.3000E+03
Avg5.2722E+033.8404E+033.7365E+034.0317E+032.4357E+034.2838E+033.3425E+032.4892E+03
Std2.2308E+031.9855E+031.4409E+032.3439E+031.7241E+022.2360E+031.8245E+037.3176E+02
Rank85461732
F22Best2.8757E+032.7724E+032.7939E+032.8340E+032.6626E+032.7538E+032.7725E+032.6611E+03
Avg2.9241E+032.8348E+032.8377E+032.8858E+032.7156E+032.8427E+032.8402E+032.6858E+03
Std5.1046E+014.9513E+012.8745E+014.1342E+012.7234E+016.6398E+014.8614E+012.3121E+01
Rank83472651
F23Best2.9973E+032.9517E+032.9748E+032.9414E+032.8469E+032.8932E+032.9091E+032.8326E+03
Avg3.0785E+033.0189E+033.0171E+033.0169E+032.8805E+032.9699E+032.9674E+032.8743E+03
Std4.9058E+017.3977E+014.6858E+015.1718E+013.3433E+015.0838E+015.3107E+013.4835E+01
Rank87652431
F24Best3.1117E+032.8935E+032.9100E+032.9610E+032.8858E+032.8751E+032.8752E+032.8755E+03
Avg3.3040E+032.9302E+032.9345E+033.0151E+032.9057E+032.8774E+032.8771E+032.8831E+03
Std1.6689E+024.1794E+014.7959E+013.8322E+011.7430E+012.5243E+003.2926E+001.6523E+01
Rank85674213
F25Best5.3487E+033.1305E+033.3116E+035.3269E+033.2700E+032.9000E+034.6602E+033.5533E+03
Avg6.6579E+034.8493E+035.2204E+035.8677E+034.1412E+034.9630E+035.3942E+033.9352E+03
Std6.6267E+021.0060E+037.6924E+025.0783E+024.0722E+021.4750E+035.1564E+022.2284E+02
Rank83572461
F26Best3.2547E+033.2176E+033.2233E+033.2314E+033.2085E+033.1688E+033.1636E+033.1264E+03
Avg3.3182E+033.2536E+033.2488E+033.2872E+033.2505E+033.1979E+033.1936E+033.1792E+03
Std3.7827E+013.0498E+012.5436E+014.4111E+013.1063E+018.0688E+001.3284E+011.8144E+01
Rank86475321
F27Best3.4442E+033.2703E+033.2752E+033.3682E+033.2251E+033.1000E+033.1000E+033.1000E+03
Avg4.2056E+033.3369E+033.3592E+033.5233E+033.2808E+033.1507E+033.1227E+033.1320E+03
Std6.9418E+026.6577E+018.3898E+011.1054E+023.6798E+017.8381E+014.7573E+015.6754E+01
Rank85674312
F28Best4.1256E+033.6850E+033.6488E+033.7986E+033.4876E+033.4398E+033.5460E+033.3836E+03
Avg4.5468E+033.9772E+034.0779E+034.4144E+033.6942E+034.0674E+034.1826E+033.5263E+03
Std2.2051E+021.7627E+023.8359E+023.5171E+021.6609E+022.9184E+023.4894E+029.7478E+01
Rank83572461
F29Best1.5259E+061.4114E+043.0712E+042.2365E+058.9715E+033.3970E+033.4184E+033.4105E+03
Avg1.5448E+077.0342E+041.3357E+052.0004E+062.1761E+044.0381E+034.3288E+033.7782E+03
Std1.9800E+075.8297E+041.9060E+051.7810E+061.1941E+041.3977E+031.6741E+033.7754E+02
Rank85674231
Table A11. Experiments comparing EECO with different strategies (50D).
Table A11. Experiments comparing EECO with different strategies (50D).
No.IndexECOECO-RECO-PECO-TECO-RPECO-RTECO-PTEECO
F1Best1.4874E+101.7123E+091.6333E+093.8342E+094.6351E+081.0000E+021.0000E+021.0000E+02
Avg2.9614E+109.8341E+098.8323E+098.3151E+091.1693E+091.0000E+021.0000E+021.0000E+02
Std1.5809E+109.7645E+099.6953E+093.0841E+097.0789E+084.3406E-069.5542E-067.7591E-08
Rank87654231
F2Best8.6958E+041.3413E+041.7793E+044.0427E+041.1476E+043.0000E+023.0006E+023.0000E+02
Avg1.1643E+053.0235E+042.7543E+045.6692E+041.8150E+043.0000E+023.1669E+023.0000E+02
Std2.9299E+041.0143E+041.0143E+041.1521E+045.1606E+032.1733E-054.3195E+011.0301E-08
Rank86574231
F3Best2.7984E+038.2303E+027.2959E+029.1188E+026.0870E+024.0000E+024.0000E+024.0000E+02
Avg4.8313E+031.2752E+031.0869E+031.5008E+037.0146E+024.0100E+024.0335E+024.0199E+02
Std1.7254E+037.0589E+026.0638E+023.6545E+021.0995E+021.8454E+005.6149E+002.1309E+00
Rank86574132
F4Best8.1635E+028.2108E+028.2996E+027.9781E+027.3342E+026.9402E+027.0297E+025.4676E+02
Avg9.6664E+028.5429E+028.7278E+028.8026E+027.8505E+027.9612E+027.8916E+025.7935E+02
Std7.3984E+012.7265E+013.6789E+015.0990E+013.0231E+017.3018E+015.0677E+012.5971E+01
Rank85672431
F5Best6.5941E+026.2107E+026.1759E+026.5943E+026.1138E+026.4507E+026.4595E+026.0232E+02
Avg6.7160E+026.2904E+026.2871E+026.6862E+026.1788E+026.5061E+026.5496E+026.0987E+02
Std8.1593E+005.2394E+006.4558E+005.7197E+005.4146E+005.0228E+004.4183E+003.7701E+00
Rank84372561
F6Best1.3615E+031.0351E+031.0313E+031.3257E+039.8508E+021.1267E+031.1796E+038.0582E+02
Avg1.6051E+031.1570E+031.1891E+031.4802E+031.0949E+031.2739E+031.3760E+038.7598E+02
Std1.5625E+027.3118E+011.0628E+029.2225E+017.6483E+018.4439E+011.1379E+027.8800E+01
Rank83472561
F7Best1.2552E+031.1264E+031.0823E+031.0244E+031.0105E+031.0209E+039.8705E+028.3582E+02
Avg1.3222E+031.1789E+031.1675E+031.1122E+031.0671E+031.1046E+031.0423E+038.6753E+02
Std5.8474E+012.9432E+014.1376E+015.7318E+014.6133E+016.1297E+013.5181E+012.2648E+01
Rank87653421
F8Best1.6640E+041.7049E+032.5857E+039.2717E+032.5501E+037.5756E+035.8310E+031.0153E+03
Avg2.1625E+044.8220E+036.0812E+031.5193E+043.5753E+031.0058E+048.4329E+031.6855E+03
Std6.6129E+034.2760E+036.3383E+036.0349E+031.1918E+032.1674E+031.9709E+034.7646E+02
Rank83472651
F9Best1.0599E+041.1526E+041.2637E+041.0489E+041.0624E+046.2082E+036.8800E+036.4855E+03
Avg1.2343E+041.3299E+041.3972E+041.1267E+041.2558E+047.5381E+038.2826E+037.4470E+03
Std1.2418E+031.3735E+037.6840E+026.5535E+021.2915E+036.5971E+021.0427E+038.5769E+02
Rank57846231
F10Best2.6975E+031.3878E+031.3264E+031.8208E+031.2738E+031.2572E+031.2313E+031.1786E+03
Avg7.5659E+031.6097E+031.6201E+032.2931E+031.3425E+031.3175E+031.3173E+031.2298E+03
Std4.5208E+032.3855E+023.9884E+023.8392E+025.9890E+014.2936E+016.7230E+013.4289E+01
Rank85674321
F11Best1.9510E+098.3336E+063.7849E+061.5806E+081.7923E+062.8989E+034.6668E+032.3988E+03
Avg4.4511E+095.9950E+077.7960E+073.3635E+087.4344E+065.8561E+032.5439E+043.8381E+03
Std3.5347E+096.0746E+071.3398E+081.9894E+084.9164E+062.2055E+032.0190E+046.6394E+02
Rank85674231
F12Best4.7945E+074.7905E+044.9773E+047.3866E+041.0358E+043.0276E+034.9996E+032.5129E+03
Avg4.2634E+082.1170E+051.1106E+065.7909E+051.7891E+043.3130E+038.1830E+033.0418E+03
Std4.9571E+082.2248E+051.7696E+064.6714E+057.6117E+033.6544E+023.1187E+034.0548E+02
Rank85764231
F13Best1.1669E+051.6854E+031.7699E+032.2665E+031.4874E+031.6111E+031.9524E+031.4956E+03
Avg8.4291E+052.7260E+033.7072E+038.1511E+041.5945E+031.8441E+034.6066E+031.5629E+03
Std8.8990E+052.6112E+034.6656E+036.7338E+046.6744E+011.5945E+024.7739E+035.6328E+01
Rank84572361
F14Best9.5511E+045.6021E+031.0829E+042.5769E+042.3075E+031.6696E+031.8519E+031.6450E+03
Avg4.1685E+061.7395E+043.4837E+041.1045E+052.7369E+032.2358E+034.2873E+031.7827E+03
Std4.8105E+066.2062E+032.7374E+041.6313E+053.1011E+027.2906E+023.5472E+036.5285E+01
Rank85673241
F15Best3.2636E+032.8973E+033.0888E+033.3822E+032.1358E+033.0117E+032.7560E+031.7416E+03
Avg4.3534E+033.5177E+033.7788E+034.2558E+032.5847E+033.5861E+033.6697E+031.9631E+03
Std7.7063E+026.2110E+024.8045E+024.4748E+023.0049E+023.8581E+024.1430E+021.2251E+02
Rank83672451
F16Best3.1359E+032.7466E+033.0389E+032.8693E+032.1334E+032.8187E+032.8073E+031.9354E+03
Avg3.8276E+033.3290E+033.4925E+033.6193E+032.6443E+033.5093E+033.5675E+032.0508E+03
Std4.5072E+024.9808E+022.8293E+024.2762E+023.9745E+025.0125E+024.0066E+028.9304E+01
Rank83472561
F17Best3.5091E+061.0936E+042.1723E+041.1425E+052.1375E+031.9784E+032.3083E+031.9169E+03
Avg1.1216E+072.4590E+043.8602E+041.3543E+066.0302E+032.3890E+032.1475E+042.0283E+03
Std1.3490E+071.1247E+041.6974E+041.1766E+065.8596E+034.6908E+022.4402E+048.3522E+01
Rank85673241
F18Best4.1986E+058.0106E+039.3311E+032.2059E+042.0721E+032.2270E+035.2715E+032.0234E+03
Avg7.3520E+063.1345E+042.4770E+042.8562E+052.6649E+032.9938E+031.4985E+042.0971E+03
Std1.2712E+073.2994E+041.4089E+043.8331E+051.2428E+031.2753E+036.4999E+035.8685E+01
Rank86572341
F19Best3.3478E+032.8489E+032.8556E+032.9419E+032.3714E+032.7335E+032.8232E+032.0586E+03
Avg3.5609E+033.5067E+033.4662E+033.3297E+033.0750E+033.2558E+033.2011E+032.2240E+03
Std2.4162E+024.4595E+022.8919E+021.9881E+023.7567E+022.3997E+021.8083E+023.0035E+02
Rank87652431
F20Best2.6066E+032.5936E+032.6141E+032.5781E+032.4538E+032.4566E+032.5187E+032.3290E+03
Avg2.7280E+032.6639E+032.6577E+032.6625E+032.5206E+032.5676E+032.5910E+032.3535E+03
Std9.3109E+014.2170E+013.4769E+016.3651E+014.0789E+017.1380E+015.6310E+011.3533E+01
Rank87562341
F21Best1.3298E+041.2450E+041.3912E+041.0328E+041.1350E+048.5844E+037.6036E+035.0448E+03
Avg1.4634E+041.4875E+041.5332E+041.2361E+041.3203E+049.6616E+039.4985E+037.6899E+03
Std9.9210E+021.1235E+037.2527E+021.1897E+031.5122E+036.9669E+021.0203E+031.7365E+03
Rank67845321
F22Best3.3141E+032.9880E+033.0555E+033.0071E+032.8528E+033.0951E+032.9323E+032.8043E+03
Avg3.3923E+033.0999E+033.1313E+033.1753E+032.9410E+033.1631E+033.0839E+032.8293E+03
Std7.9087E+016.0151E+015.4227E+011.3935E+027.0170E+017.7899E+011.3450E+022.4471E+01
Rank84572631
F23Best3.3913E+033.2301E+033.1913E+033.1977E+033.0424E+033.1700E+033.1203E+032.9313E+03
Avg3.4727E+033.3223E+033.3158E+033.3363E+033.0782E+033.2764E+033.2253E+032.9771E+03
Std5.6544E+017.0301E+017.3889E+018.9988E+013.9342E+017.1199E+018.7769E+013.1910E+01
Rank86572431
F24Best4.0832E+033.1133E+033.1674E+033.4361E+033.0852E+032.9312E+032.9312E+032.9312E+03
Avg5.6884E+033.2933E+033.4664E+033.9312E+033.2246E+032.9484E+032.9510E+032.9704E+03
Std1.1749E+031.3212E+023.8706E+023.2416E+021.1465E+022.8327E+012.1151E+015.5206E+01
Rank85674123
F25Best9.4028E+034.6049E+034.9863E+038.1750E+034.6817E+032.9000E+036.8057E+032.9000E+03
Avg1.0666E+049.3013E+039.1580E+039.5167E+035.4805E+036.9772E+038.6172E+035.1016E+03
Std1.0610E+032.8115E+032.6140E+031.0717E+036.6492E+022.6369E+031.0896E+031.6157E+03
Rank86572341
F26Best3.7640E+033.5132E+033.5289E+033.5667E+033.4597E+033.2000E+033.2000E+033.2000E+03
Avg3.8678E+033.7966E+033.6723E+033.7331E+033.6828E+033.2000E+033.2877E+033.2832E+03
Std1.0946E+021.9632E+021.2993E+029.3677E+011.7884E+022.3037E-041.5233E+021.1593E+02
Rank87465132
F27Best5.7906E+033.5320E+033.5273E+033.9688E+033.4223E+033.3000E+033.3000E+033.3000E+03
Avg6.9434E+033.9976E+034.0915E+035.2151E+033.7022E+033.3000E+033.3000E+033.3000E+03
Std1.0679E+036.6630E+026.2240E+021.7850E+033.2882E+022.8917E-044.3785E-042.3095E-04
Rank85674213
F28Best4.8206E+034.0169E+034.6036E+034.8315E+033.7132E+034.0221E+033.8569E+033.2792E+03
Avg5.9201E+034.5784E+034.9916E+035.6036E+033.9604E+034.6594E+034.6112E+033.5197E+03
Std9.7895E+023.9747E+023.2822E+025.3689E+022.4007E+023.6165E+024.3303E+021.7277E+02
Rank83672541
F29Best7.6148E+075.9299E+065.7643E+069.7692E+064.1470E+063.5642E+034.2650E+033.7023E+03
Avg1.1956E+081.6112E+071.6586E+073.3596E+076.5852E+064.4847E+037.3233E+034.9940E+03
Std4.7460E+079.4964E+067.7069E+061.6651E+074.3394E+061.1864E+032.5869E+038.4520E+02
Rank85674132
Table A12. Experiments comparing EECO with different strategies (100D).
Table A12. Experiments comparing EECO with different strategies (100D).
No.IndexECOECO-RECO-PECO-TECO-RPECO-RTECO-PTEECO
F1Best1.0516E+113.0095E+103.1271E+104.1183E+101.5766E+101.0000E+021.0000E+021.0000E+02
Avg1.1103E+115.2045E+105.0924E+104.6461E+102.1746E+101.0003E+021.0001E+021.0000E+02
Std4.9348E+092.0849E+101.8951E+105.7708E+094.8158E+096.0942E-022.4349E-026.4717E-06
Rank87654321
F2Best2.5917E+057.4127E+048.5360E+041.7383E+056.1414E+043.0000E+023.1346E+033.0000E+02
Avg2.8050E+051.0376E+051.1663E+051.8919E+057.1423E+043.0007E+025.9298E+033.0000E+02
Std2.5113E+042.6599E+043.1513E+042.1177E+047.5450E+037.9467E-023.6469E+032.1971E-06
Rank85674231
F3Best1.1491E+042.1286E+033.0027E+032.8217E+031.9486E+034.0002E+025.0524E+024.0000E+02
Avg1.6719E+043.2376E+035.2968E+035.7124E+033.0397E+034.0201E+025.3509E+024.0100E+02
Std8.1866E+037.4036E+024.0948E+032.8925E+038.4657E+022.2839E+002.6686E+011.9933E+00
Rank85674231
F4Best1.5748E+031.2840E+031.3118E+031.3241E+031.2387E+031.1666E+031.1039E+037.2685E+02
Avg1.6415E+031.3965E+031.4168E+031.4724E+031.3059E+031.2034E+031.2412E+037.7287E+02
Std4.5651E+019.8467E+017.1990E+011.3526E+026.6340E+014.4628E+011.2893E+023.9702E+01
Rank85674231
F5Best6.7534E+026.3345E+026.4480E+026.7409E+026.2185E+026.5284E+026.5792E+026.1417E+02
Avg6.7727E+026.4381E+026.5320E+026.8050E+026.2960E+026.5748E+026.6026E+026.1620E+02
Std1.9568E+008.6019E+007.1155E+004.7358E+006.5724E+005.4894E+002.7109E+001.4088E+00
Rank73482561
F6Best3.1609E+032.0400E+031.8295E+032.5417E+031.7047E+032.4412E+032.2132E+031.1324E+03
Avg3.2687E+032.0882E+032.0493E+032.9158E+031.9189E+032.6823E+032.5437E+031.4027E+03
Std1.3907E+023.9495E+011.4911E+022.8265E+021.6912E+022.1764E+022.7580E+022.5504E+02
Rank84372651
F7Best1.8844E+031.6015E+031.6520E+031.6237E+031.3535E+031.5184E+031.3850E+039.4725E+02
Avg2.0902E+031.6806E+031.7266E+031.8038E+031.5402E+031.5522E+031.5417E+031.0709E+03
Std1.5760E+025.9198E+018.7412E+011.5709E+021.5571E+024.2327E+011.5035E+029.9907E+01
Rank85672431
F8Best4.8102E+041.4406E+041.4183E+042.6799E+041.0715E+041.6519E+041.5908E+044.3083E+03
Avg5.6594E+041.8187E+041.8627E+043.8813E+041.3069E+041.9516E+041.8307E+045.1535E+03
Std6.9367E+034.5297E+033.1164E+039.8444E+033.2253E+032.0485E+033.0703E+037.2934E+02
Rank83572641
F9Best2.5800E+042.7285E+042.7926E+042.0376E+041.9588E+041.5219E+041.5109E+041.4432E+04
Avg2.7131E+042.9396E+042.9808E+042.2490E+042.5476E+041.6132E+041.5729E+041.6239E+04
Std1.5785E+031.4523E+031.9246E+031.4374E+033.9830E+038.9264E+025.0605E+021.2876E+03
Rank67845213
F10Best5.0265E+043.3547E+034.5879E+031.1749E+043.2895E+032.0611E+032.0025E+031.9029E+03
Avg8.1274E+044.7507E+036.6031E+031.9530E+044.0586E+032.3093E+032.4283E+032.1138E+03
Std3.9368E+041.2202E+031.6881E+036.0838E+036.9905E+023.5187E+023.9237E+021.9880E+02
Rank85674231
F11Best1.9040E+106.2793E+086.2023E+081.5924E+091.5848E+086.8913E+037.9901E+045.6050E+03
Avg2.7304E+104.2740E+091.0329E+093.0342E+092.7863E+081.3951E+044.8239E+056.2549E+03
Std6.5837E+097.0913E+093.7283E+082.3360E+098.0207E+071.0682E+044.3477E+056.7961E+02
Rank87564231
F12Best4.4658E+089.9737E+045.8450E+052.9253E+063.3295E+045.2264E+038.6177E+034.4995E+03
Avg1.7600E+096.8901E+055.0099E+061.5838E+074.9695E+045.7215E+031.2482E+045.4561E+03
Std1.0977E+097.3069E+053.7033E+069.2656E+061.6833E+043.3285E+026.7082E+037.5747E+02
Rank85674231
F13Best2.4685E+064.3975E+031.0048E+047.5838E+051.9051E+031.8910E+038.0619E+041.6668E+03
Avg9.9605E+064.3691E+042.7520E+041.4399E+061.9514E+031.9718E+031.2106E+051.7312E+03
Std1.1653E+074.1511E+041.8330E+045.1181E+054.1764E+018.2902E+015.6113E+045.7043E+01
Rank85472361
F14Best8.5045E+072.3734E+047.7999E+042.3842E+054.3368E+031.7363E+033.6125E+031.7283E+03
Avg1.4398E+081.3860E+056.3094E+055.9576E+051.4861E+042.1163E+038.6434E+031.8265E+03
Std6.2725E+071.5569E+051.0637E+065.3556E+057.5104E+033.6610E+026.6372E+031.2393E+02
Rank85764231
F15Best8.9502E+036.5134E+038.8078E+037.3823E+035.8130E+035.1252E+035.4745E+032.3725E+03
Avg9.3818E+038.2152E+038.9009E+037.8220E+036.2840E+035.4526E+036.2043E+032.6452E+03
Std4.4861E+021.1734E+031.5465E+023.5841E+025.7924E+023.5077E+025.1416E+022.7448E+02
Rank86754231
F16Best6.3541E+034.6568E+035.2042E+034.8201E+035.0372E+035.3604E+034.8585E+032.4919E+03
Avg8.3109E+035.9415E+036.1256E+035.9874E+035.3528E+036.2674E+035.8825E+032.6102E+03
Std2.3441E+031.2160E+036.7674E+021.0010E+033.9766E+027.1808E+029.3651E+021.0639E+02
Rank84652731
F17Best1.8859E+064.3167E+041.0863E+057.8303E+053.5819E+032.0733E+035.5668E+041.9816E+03
Avg7.1368E+068.0853E+041.4492E+051.5538E+069.7584E+032.3476E+038.1009E+042.0734E+03
Std4.2842E+063.9796E+043.8905E+041.3845E+066.9019E+033.4047E+021.8989E+048.7551E+01
Rank84673251
F18Best1.6028E+084.4227E+059.9918E+052.3379E+064.9476E+032.4134E+033.7153E+032.1091E+03
Avg4.5686E+082.0186E+064.8011E+064.7988E+061.0695E+054.3452E+031.1482E+042.1934E+03
Std3.6604E+081.7077E+065.9593E+062.5721E+061.9393E+051.7139E+037.2586E+037.9347E+01
Rank85764231
F19Best4.7506E+035.1288E+036.4699E+035.6490E+035.1299E+034.5121E+035.0852E+032.4849E+03
Avg5.9860E+036.3524E+036.6515E+036.0029E+035.3720E+035.0431E+035.5031E+033.5464E+03
Std8.9336E+028.9209E+021.9080E+023.2796E+022.9674E+026.0944E+024.8821E+021.2969E+03
Rank57863241
F20Best3.5372E+033.1177E+033.1813E+033.3691E+032.9001E+033.0169E+033.1617E+032.5136E+03
Avg3.6555E+033.2395E+033.2885E+033.5420E+033.0209E+033.1326E+033.3213E+032.5938E+03
Std9.5124E+019.9611E+017.2293E+011.7597E+021.1162E+027.7493E+011.4275E+028.3624E+01
Rank84572361
F21Best2.8975E+042.7443E+043.1073E+042.5257E+042.6838E+041.7014E+041.6261E+047.2030E+03
Avg3.0308E+043.0554E+043.2512E+042.7318E+042.9010E+041.9066E+041.8500E+041.3637E+04
Std1.1579E+032.2007E+039.6970E+021.5657E+031.7959E+031.6758E+032.3146E+035.5275E+03
Rank67845321
F22Best4.0146E+033.7717E+033.7810E+033.8955E+033.6365E+033.8335E+033.6315E+033.1159E+03
Avg4.4003E+033.8149E+033.9304E+034.1166E+033.7299E+033.9677E+033.8219E+033.1517E+03
Std2.7683E+024.6466E+011.1741E+021.9481E+021.0615E+021.7590E+021.7212E+023.2483E+01
Rank83572641
F23Best4.8007E+034.3135E+034.2658E+034.9132E+034.3763E+034.3493E+034.5250E+034.0159E+03
Avg5.1692E+034.7310E+034.6800E+034.9646E+034.6214E+034.7365E+034.5705E+034.3151E+03
Std2.7420E+025.8390E+024.9537E+025.8790E+012.6404E+023.8043E+024.6508E+013.2444E+02
Rank85473621
F24Best9.5292E+034.6765E+034.6027E+036.4767E+034.1720E+033.1786E+033.1528E+033.1422E+03
Avg1.1884E+045.7583E+035.5506E+036.6788E+034.6597E+033.2697E+033.2063E+033.2219E+03
Std2.4724E+037.7302E+028.7766E+022.1784E+024.6581E+021.0042E+024.6358E+015.4176E+01
Rank86574312
F25Best2.0470E+041.5487E+041.6172E+041.8679E+041.2736E+041.4539E+041.6263E+049.1279E+03
Avg2.5238E+041.8591E+041.8351E+042.0598E+041.3736E+041.9982E+041.7532E+049.3409E+03
Std3.9562E+034.8713E+033.5792E+031.5874E+031.0458E+035.0807E+031.4224E+032.2093E+02
Rank85472631
F26Best4.0171E+033.7632E+033.9673E+033.7508E+033.8525E+033.2000E+033.1738E+033.2000E+03
Avg4.4848E+034.0831E+034.1337E+034.1520E+033.9812E+033.5778E+033.4184E+033.4063E+03
Std6.6520E+022.9851E+021.1852E+023.3224E+021.6569E+023.2713E+023.5035E+022.5661E+02
Rank85674321
F27Best1.0026E+045.8808E+035.7947E+036.1947E+034.7823E+033.2874E+033.2898E+033.2874E+03
Avg1.7443E+049.4214E+037.4928E+038.5150E+035.5494E+033.2953E+033.3133E+033.3058E+03
Std5.0251E+034.7589E+031.4923E+031.6129E+031.3058E+038.8779E+001.6900E+011.7743E+01
Rank87564132
F28Best1.2195E+047.9610E+038.4826E+039.7899E+036.6392E+035.8516E+036.9908E+034.0686E+03
Avg1.4170E+048.9221E+039.2074E+031.0293E+047.3185E+036.7316E+037.3267E+034.4266E+03
Std2.8708E+036.6130E+026.0040E+023.9135E+026.9860E+029.6459E+023.6017E+024.6202E+02
Rank85673241
F29Best5.5469E+081.6549E+079.1512E+066.3844E+071.2371E+064.5489E+035.4792E+034.1986E+03
Avg7.5685E+082.5576E+071.4285E+089.1258E+077.4923E+064.8361E+031.0472E+044.3872E+03
Std1.6456E+089.2373E+062.3804E+082.7638E+071.0097E+072.0753E+024.4159E+031.9108E+02
Rank85764231
Table A13. Experiments comparing EECO with other competing algorithms (10D).
Table A13. Experiments comparing EECO with other competing algorithms (10D).
No.IndexEECOEDECOISGTOAAPSM-jSOLSHADE-SPACMAEOSMAGLSRIMEEPSCAESLPSO
F1Best1.0000E+023.6458E+051.2219E+044.3728E+022.1982E+046.6664E+061.4381E+041.2102E+029.5769E+03
Avg1.0000E+024.6495E+066.8504E+043.1539E+034.0940E+041.8883E+077.2018E+051.5336E+034.1541E+04
Std0.0000E+003.8003E+063.5297E+042.3017E+031.3861E+041.5049E+071.1249E+061.3630E+032.7714E+04
Rank186349725
F2Best3.0000E+023.3388E+021.1758E+033.0003E+023.0000E+021.3322E+033.2315E+023.1696E+021.1840E+03
Avg3.0000E+027.8825E+023.2470E+033.0046E+023.0032E+022.7750E+034.8869E+021.0581E+032.1846E+03
Std0.0000E+004.7027E+021.4896E+038.4502E-014.9203E-011.0708E+031.3797E+021.2131E+037.0420E+02
Rank159328467
F3Best4.0000E+024.0058E+024.0376E+024.0345E+024.0300E+024.0660E+024.0109E+024.0554E+024.0407E+02
Avg4.0000E+024.0632E+024.1345E+024.0440E+024.0387E+024.0868E+024.0636E+024.1103E+024.0594E+02
Std4.1355E-133.0294E+002.2317E+016.7479E-014.3237E-011.4331E+002.1195E+001.6160E+017.6909E-01
Rank159327684
F4Best5.0199E+025.1145E+025.2820E+025.2013E+025.1273E+025.2306E+025.0732E+025.0398E+025.2666E+02
Avg5.0451E+025.2516E+025.3830E+025.3318E+025.2649E+025.3236E+025.1956E+025.1131E+025.3437E+02
Std1.7983E+001.0200E+016.8853E+007.9570E+006.0967E+004.3687E+008.4660E+006.7448E+004.3431E+00
Rank149756328
F5Best6.0000E+026.0201E+026.0035E+026.0008E+026.0041E+026.0312E+026.0045E+026.0000E+026.0011E+02
Avg6.0001E+026.0704E+026.0129E+026.0024E+026.0096E+026.0625E+026.0124E+026.0001E+026.0017E+02
Std3.7882E-025.9222E+001.4108E+001.2920E-012.7884E-012.1039E+001.0194E+001.1405E-025.0284E-02
Rank197458623
F6Best7.1089E+027.3103E+027.3385E+027.3895E+027.3565E+027.3668E+027.2249E+027.1345E+027.3729E+02
Avg7.1422E+027.4554E+027.4796E+027.4543E+027.4457E+027.5149E+027.3151E+027.2013E+027.4561E+02
Std3.3408E+009.9181E+007.4978E+004.6171E+005.7293E+007.1197E+005.3489E+004.6793E+005.0158E+00
Rank168549327
F7Best8.0199E+028.1484E+028.1718E+028.2414E+028.2062E+028.1715E+028.0500E+028.0398E+028.2633E+02
Avg8.0829E+028.3283E+028.3223E+028.3274E+028.3068E+028.3053E+028.1646E+028.0842E+028.3372E+02
Std4.8839E+001.0619E+019.4331E+006.7384E+004.4348E+007.4438E+006.9962E+003.3185E+004.2053E+00
Rank186754329
F8Best9.0000E+029.0197E+029.0004E+029.0000E+029.0021E+029.0564E+029.0028E+029.0000E+029.0001E+02
Avg9.0000E+029.2277E+029.0075E+029.0005E+029.0049E+029.2748E+029.0333E+029.0021E+029.0003E+02
Std0.0000E+002.0248E+011.5514E+005.9482E-022.4618E-011.7200E+015.5906E+004.5959E-011.6631E-02
Rank186359742
F9Best1.3769E+031.6057E+031.7620E+032.1993E+031.8103E+031.7452E+031.3686E+031.0424E+032.2841E+03
Avg1.6773E+032.1169E+032.2447E+032.5286E+032.2331E+032.2384E+031.6846E+031.5869E+032.6105E+03
Std1.9887E+023.5449E+022.7255E+021.7634E+022.4051E+021.8060E+022.7235E+023.1790E+021.9291E+02
Rank247856319
F10Best1.1010E+031.1074E+031.1140E+031.1053E+031.1083E+031.1300E+031.1073E+031.1020E+031.1064E+03
Avg1.1069E+031.1340E+031.1299E+031.1102E+031.1115E+031.1394E+031.1305E+031.1065E+031.1091E+03
Std6.5809E+001.4243E+018.5493E+003.5789E+002.9111E+008.5438E+004.8719E+014.2456E+002.0175E+00
Rank286459713
F11Best1.3186E+036.6787E+034.5962E+041.4754E+033.3895E+032.4878E+056.4074E+043.3699E+032.2412E+04
Avg1.5028E+034.2079E+051.1059E+063.1059E+036.3668E+031.3828E+062.2778E+062.2763E+041.9604E+05
Std2.0539E+028.0888E+051.2438E+062.0520E+032.4259E+031.1314E+062.2053E+062.2717E+041.4326E+05
Rank167238945
F12Best1.3054E+031.4321E+032.1589E+031.3156E+031.3333E+031.9172E+031.5638E+031.3323E+031.4027E+03
Avg1.4125E+032.3128E+037.3130E+031.3294E+031.3670E+034.1934E+031.2210E+048.3471E+031.6581E+03
Std1.3790E+026.4454E+025.0782E+037.3498E+002.8269E+011.7121E+031.0244E+048.1296E+031.6882E+02
Rank357126984
F13Best1.4010E+031.4353E+031.4545E+031.4225E+031.4229E+031.4705E+031.4368E+031.4392E+031.4297E+03
Avg1.4181E+031.4464E+031.5066E+031.4287E+031.4302E+031.5018E+033.5312E+033.5011E+031.4380E+03
Std1.2380E+011.0283E+013.2996E+013.7559E+003.3408E+002.4954E+013.6441E+032.5436E+036.3816E+00
Rank157236984
F14Best1.5012E+031.5213E+031.6320E+031.5036E+031.5039E+031.6968E+031.5405E+031.5063E+031.5128E+03
Avg1.5070E+031.5734E+032.3545E+031.5090E+031.5100E+031.9809E+035.5340E+035.7982E+031.5214E+03
Std7.3589E+003.3017E+018.2288E+023.1159E+003.5437E+001.9851E+025.5043E+035.7461E+037.3901E+00
Rank157236894
F15Best1.6006E+031.6471E+031.6436E+031.6113E+031.6302E+031.6231E+031.6030E+031.6008E+031.6197E+03
Avg1.6043E+031.7534E+031.7322E+031.6602E+031.6760E+031.6914E+031.7153E+031.6830E+031.6520E+03
Std5.0260E+008.5112E+016.0279E+014.3422E+013.5946E+015.6376E+011.0285E+025.9611E+012.8193E+01
Rank198346752
F16Best1.7017E+031.7517E+031.7503E+031.7465E+031.7478E+031.7511E+031.7233E+031.7020E+031.7488E+03
Avg1.7299E+031.7843E+031.7777E+031.7707E+031.7625E+031.7679E+031.7636E+031.7489E+031.7684E+03
Std1.9279E+012.5266E+011.8614E+011.5112E+018.6480E+001.1129E+015.2163E+013.3815E+011.1755E+01
Rank198735426
F17Best1.8020E+031.8977E+034.1121E+031.8262E+031.8429E+034.3540E+031.9697E+035.8071E+032.0069E+03
Avg1.8248E+032.6442E+031.6903E+041.8374E+031.8634E+039.7821E+031.5212E+041.7820E+042.4293E+03
Std1.3687E+011.5209E+031.3677E+042.1320E+011.1244E+014.9377E+031.0553E+041.4949E+044.2057E+02
Rank158236794
F18Best1.9001E+031.9076E+031.9427E+031.9031E+031.9056E+031.9591E+031.9893E+032.0423E+031.9070E+03
Avg1.9023E+031.9314E+032.9291E+031.9061E+031.9078E+032.1764E+031.2075E+041.2054E+041.9171E+03
Std1.4866E+002.6537E+011.3349E+031.4331E+001.2419E+001.9583E+029.1351E+039.8731E+031.6817E+01
Rank157236984
F19Best2.0003E+032.0572E+032.0407E+032.0288E+032.0420E+032.0510E+032.0083E+032.0043E+032.0365E+03
Avg2.0217E+032.1072E+032.0880E+032.0608E+032.0537E+032.0812E+032.0325E+032.0544E+032.0695E+03
Std1.2913E+013.2708E+014.8633E+011.6134E+018.2472E+001.4757E+011.5923E+015.1969E+012.4319E+01
Rank198537246
F20Best2.2000E+032.2045E+032.2028E+032.2011E+032.2051E+032.2045E+032.2028E+032.2026E+032.2011E+03
Avg2.2711E+032.2649E+032.2646E+032.2934E+032.2385E+032.2126E+032.2586E+032.2767E+032.2729E+03
Std5.0488E+015.9235E+016.3947E+015.9428E+014.0454E+016.3692E+006.1027E+015.2795E+016.8836E+01
Rank654921387
F21Best2.2000E+032.2223E+032.2121E+032.3005E+032.3030E+032.2347E+032.2420E+032.3004E+032.2004E+03
Avg2.2882E+032.2853E+032.3010E+032.3040E+032.3058E+032.2929E+032.3037E+032.3013E+032.2968E+03
Std3.1550E+013.5266E+012.4684E+012.0324E+001.1045E+002.5099E+011.7180E+016.9255E-012.6695E+01
Rank215893764
F22Best2.6043E+032.6119E+032.6158E+032.6173E+032.6226E+032.6252E+032.6100E+032.6049E+032.6205E+03
Avg2.6083E+032.6306E+032.6318E+032.6267E+032.6270E+032.6339E+032.6186E+032.6152E+032.6316E+03
Std2.7440E+001.0612E+018.8355E+007.7301E+003.8182E+006.2436E+006.1957E+006.1566E+005.6734E+00
Rank168459327
F23Best2.5000E+032.5650E+032.5292E+032.5278E+032.6075E+032.5519E+032.5015E+032.7336E+032.5017E+03
Avg2.7058E+032.7235E+032.7319E+032.7439E+032.7436E+032.6264E+032.7192E+032.7445E+032.7467E+03
Std8.3745E+016.4933E+017.6833E+016.0187E+013.9309E+016.9795E+018.8035E+017.5621E+006.7877E+01
Rank245761389
F24Best2.8977E+032.8982E+032.8997E+032.8983E+032.8983E+032.9095E+032.8993E+032.8979E+032.8978E+03
Avg2.9366E+032.9305E+032.9262E+032.9232E+032.9200E+032.9289E+032.9164E+032.9226E+032.9172E+03
Std2.9542E+012.1289E+012.3028E+012.3966E+012.3323E+011.5984E+012.3498E+012.2861E+012.3638E+01
Rank986537142
F25Best2.9000E+032.9475E+032.8323E+032.9000E+032.9004E+032.9359E+032.6252E+032.9065E+032.9002E+03
Avg2.9230E+033.0115E+032.9276E+032.9013E+032.9007E+032.9690E+032.9135E+032.9981E+032.9128E+03
Std5.3723E+013.6039E+014.4321E+014.5516E+001.4898E-012.0999E+018.7845E+012.1104E+022.1433E+01
Rank596217483
F26Best3.0884E+033.0911E+033.0899E+033.0890E+033.0902E+033.0917E+033.0886E+033.0890E+033.0890E+03
Avg3.0959E+033.0955E+033.0932E+033.0919E+033.0919E+033.0957E+033.0960E+033.0915E+033.0904E+03
Std1.0550E+012.7736E+001.8301E+002.8135E+001.8393E+002.6493E+003.2250E+002.8328E+001.8616E+00
Rank865437921
F27Best3.1000E+033.1769E+033.1708E+033.1004E+033.1015E+033.1737E+033.1162E+033.1709E+033.1059E+03
Avg3.2558E+033.3553E+033.2898E+033.2492E+033.1384E+033.1987E+033.3037E+033.3113E+033.2841E+03
Std4.7561E+017.9883E+019.3613E+011.3976E+027.7983E+012.0953E+011.2008E+021.0871E+021.2466E+02
Rank496312785
F28Best3.1285E+033.1834E+033.1613E+033.1930E+033.1784E+033.1833E+033.1528E+033.1428E+033.1789E+03
Avg3.1616E+033.2401E+033.2344E+033.2142E+033.2072E+033.2271E+033.2070E+033.1984E+033.2182E+03
Std4.3286E+013.8778E+014.3355E+011.2911E+012.1182E+012.2485E+014.2151E+015.6873E+012.9768E+01
Rank198547326
F29Best3.2239E+038.8689E+039.2557E+043.5261E+033.6195E+031.4603E+043.1605E+048.1467E+038.6256E+03
Avg3.4510E+033.2007E+055.6833E+055.8737E+044.7080E+032.1623E+054.7384E+055.1229E+057.5443E+04
Std4.7789E+022.9692E+051.9678E+052.1093E+057.9064E+022.1599E+055.4640E+054.1178E+052.2195E+05
Rank169325784
Table A14. Experiments comparing EECO with other competing algorithms (30D).
Table A14. Experiments comparing EECO with other competing algorithms (30D).
No.IndexEECOEDECOISGTOAAPSM-jSOLSHADE-SPACMAEOSMAGLSRIMEEPSCAESLPSO
F1Best1.0000E+025.3039E+081.4421E+071.2706E+051.6057E+068.7951E+083.7752E+071.5624E+065.6446E+06
Avg1.0000E+021.5110E+095.1761E+074.8320E+052.2121E+061.6162E+099.8047E+076.5408E+068.8206E+06
Std5.3627E-107.3613E+083.6068E+073.5801E+054.4854E+053.6773E+084.8338E+074.6111E+061.8781E+06
Rank186239745
F2Best3.0000E+021.2279E+043.5890E+041.7257E+031.9999E+033.8464E+042.5898E+044.0182E+044.0100E+04
Avg3.0000E+022.3419E+045.4283E+043.2838E+034.5539E+037.0305E+044.3016E+046.2530E+045.5441E+04
Std6.9834E-138.0982E+039.5103E+031.3420E+031.9824E+031.7803E+041.1870E+041.3120E+041.1653E+04
Rank146239587
F3Best4.0000E+025.9254E+025.1367E+024.8860E+024.9001E+025.9540E+025.0785E+025.0512E+024.8920E+02
Avg4.0186E+026.9028E+025.5668E+024.9975E+024.9337E+027.0082E+025.6136E+025.3020E+025.0397E+02
Std2.0587E+007.6803E+012.3905E+011.0684E+015.3051E+005.8867E+014.8030E+011.3863E+011.3118E+01
Rank186329754
F4Best5.1990E+026.4144E+026.6666E+026.5917E+026.7267E+026.6119E+025.6884E+025.3682E+026.7528E+02
Avg5.4245E+027.1821E+027.2051E+026.8949E+026.9178E+026.9167E+026.2717E+025.5117E+026.9092E+02
Std2.4699E+013.1051E+011.8445E+011.5287E+011.1377E+012.1582E+013.3323E+011.5438E+017.9229E+00
Rank189476325
F5Best6.0122E+026.1833E+026.0770E+026.0096E+026.0228E+026.1529E+026.0775E+026.0065E+026.0219E+02
Avg6.0340E+026.3018E+026.1341E+026.0126E+026.0263E+026.2206E+026.1388E+026.0116E+026.0274E+02
Std1.7467E+007.1418E+004.4624E+002.5342E-013.3298E-014.3494E+003.8657E+003.8720E-012.9200E-01
Rank596238714
F6Best7.4415E+029.3163E+029.3913E+028.9475E+029.1084E+029.3761E+028.6369E+027.6922E+029.0261E+02
Avg7.6706E+021.0130E+039.6859E+029.2613E+029.3231E+029.7383E+029.2750E+027.9502E+029.2460E+02
Std1.6126E+014.9454E+011.5065E+011.3596E+011.3158E+012.7940E+013.8331E+011.5905E+011.2106E+01
Rank197468523
F7Best8.1094E+029.0226E+029.9055E+029.6383E+029.6640E+029.5808E+028.7527E+028.3155E+029.6139E+02
Avg8.2633E+029.8250E+021.0134E+039.8336E+029.9102E+029.9176E+029.0371E+028.5138E+029.9165E+02
Std1.0768E+013.4335E+011.8101E+011.2602E+011.2600E+011.9137E+011.8473E+011.7674E+011.0220E+01
Rank149568327
F8Best9.0235E+021.8289E+031.1045E+039.0124E+029.0917E+021.5291E+031.3816E+039.1027E+029.0839E+02
Avg1.0753E+033.7534E+031.5542E+039.0458E+029.1409E+022.1229E+032.7262E+039.3821E+029.1271E+02
Std2.6070E+021.4570E+032.9598E+022.9538E+003.7457E+005.9383E+021.5440E+032.3179E+012.9297E+00
Rank596137842
F9Best4.0675E+036.5101E+037.6171E+037.4353E+037.6053E+037.1897E+033.5790E+033.4376E+037.8424E+03
Avg5.0357E+037.4975E+038.5601E+038.5088E+038.4969E+038.1087E+034.7628E+034.3311E+038.5848E+03
Std5.9698E+026.6318E+023.7719E+024.5679E+023.6219E+024.0558E+027.5565E+026.1071E+023.4561E+02
Rank348765219
F10Best1.1318E+031.2920E+031.6673E+031.1848E+031.1983E+031.5687E+031.3084E+031.1905E+031.2305E+03
Avg1.1611E+031.4184E+032.0473E+031.2381E+031.2363E+031.8812E+031.4176E+031.2341E+031.2940E+03
Std2.1430E+018.9162E+012.3458E+022.6578E+012.4724E+011.9991E+025.7595E+012.3916E+013.8506E+01
Rank179438625
F11Best1.6653E+037.8723E+061.8725E+067.4811E+044.1210E+052.2139E+075.1398E+062.2234E+051.1290E+06
Avg2.3615E+033.5060E+077.2653E+063.1591E+056.3099E+055.2438E+072.9002E+079.6314E+053.4038E+06
Std4.0135E+022.4954E+075.2816E+061.9125E+051.9221E+051.8848E+072.8836E+076.9246E+051.3689E+06
Rank186239745
F12Best1.5151E+036.8309E+045.1006E+041.3354E+047.2208E+041.2932E+061.3033E+052.3028E+033.1282E+04
Avg2.2556E+031.7408E+051.0671E+052.4361E+041.1064E+055.9791E+066.4118E+051.6490E+043.5679E+05
Std6.0513E+026.6446E+044.0863E+048.1766E+033.3247E+043.9361E+066.7998E+051.5310E+042.2516E+05
Rank164359827
F13Best1.4290E+031.6480E+036.2522E+031.5233E+031.7046E+038.8463E+031.7184E+041.0452E+041.9220E+03
Avg1.4809E+032.1678E+035.7616E+041.5550E+031.8528E+034.4053E+046.7324E+046.0331E+042.2141E+03
Std3.7896E+011.0257E+035.1036E+041.8277E+011.1568E+021.6550E+049.2942E+045.4731E+044.0052E+02
Rank147236985
F14Best1.5598E+031.1776E+042.1726E+042.2031E+038.3951E+031.7641E+051.1149E+041.8018E+032.8439E+04
Avg1.6608E+032.9877E+045.0011E+042.6417E+031.5391E+046.9094E+051.0579E+056.7769E+036.4259E+04
Std4.9470E+011.2842E+042.9789E+043.0961E+023.7403E+033.5046E+057.5788E+047.5208E+033.5590E+04
Rank156249837
F15Best1.6027E+032.3269E+033.0603E+032.9586E+033.0544E+032.6997E+032.1477E+031.8036E+032.9860E+03
Avg1.8519E+033.1450E+033.4625E+033.3134E+033.3023E+033.2390E+032.6645E+032.2518E+033.2904E+03
Std2.1228E+022.9881E+022.5125E+021.8615E+021.6300E+022.2390E+022.4032E+023.0237E+021.9330E+02
Rank149875326
F16Best1.7361E+032.0277E+031.9647E+032.1222E+032.1678E+031.9465E+031.8512E+031.7472E+032.1890E+03
Avg1.8085E+032.2589E+032.2186E+032.3222E+032.3369E+032.1903E+032.1164E+031.9747E+032.3484E+03
Std7.7009E+011.5197E+021.8425E+021.3377E+026.5920E+011.2145E+021.8100E+021.8146E+029.5764E+01
Rank165784329
F17Best1.8689E+032.2311E+042.1272E+053.0625E+037.4247E+033.9751E+052.0559E+054.3165E+043.3972E+04
Avg1.9368E+038.2441E+046.6926E+054.6467E+032.1219E+049.9425E+051.3957E+061.6978E+061.0076E+05
Std5.3946E+014.2900E+045.5054E+051.8981E+038.5896E+033.9903E+051.6107E+061.8392E+064.6845E+04
Rank146237895
F18Best1.9224E+038.8543E+031.1727E+042.0927E+034.4990E+032.1800E+053.4797E+042.1061E+031.6010E+04
Avg1.9971E+031.1076E+055.0607E+042.4929E+037.3318E+039.0461E+054.2046E+051.1869E+044.6635E+04
Std5.4650E+011.1407E+052.4995E+048.3597E+022.4318E+035.1692E+052.6358E+051.0936E+042.0478E+04
Rank176239845
F19Best2.0256E+032.3527E+032.3649E+032.4896E+032.3920E+032.4831E+032.1343E+032.0434E+032.5506E+03
Avg2.0490E+032.6169E+032.7130E+032.7752E+032.7295E+032.6702E+032.3856E+032.3026E+032.7614E+03
Std1.6675E+011.4438E+021.8280E+021.3137E+021.2573E+021.1245E+021.6334E+021.5163E+021.2883E+02
Rank146975328
F20Best2.3131E+032.4240E+032.4295E+032.4519E+032.4579E+032.4561E+032.3778E+032.3329E+032.4697E+03
Avg2.3354E+032.4809E+032.4909E+032.4776E+032.4851E+032.4792E+032.4279E+032.3474E+032.4859E+03
Std2.8757E+012.9743E+012.6470E+011.4645E+011.2279E+011.3616E+012.7676E+011.1543E+017.8237E+00
Rank169475328
F21Best2.3000E+032.6673E+032.3304E+032.3114E+032.3171E+032.6017E+032.3303E+032.3172E+032.3190E+03
Avg2.4892E+036.1441E+032.9698E+032.3146E+032.3185E+032.6679E+034.6361E+035.2111E+032.3324E+03
Std7.3176E+023.0103E+032.0063E+031.8596E+009.4974E-014.2942E+012.1822E+031.6268E+032.9509E+01
Rank496125783
F22Best2.6611E+032.7771E+032.8080E+032.8176E+032.8092E+032.8073E+032.7374E+032.6827E+032.8209E+03
Avg2.6858E+032.8699E+032.8557E+032.8372E+032.8386E+032.8516E+032.7733E+032.6964E+032.8404E+03
Std2.3121E+013.3452E+012.0868E+011.3129E+011.2770E+012.4432E+012.1428E+011.0057E+019.0912E+00
Rank198457326
F23Best2.8326E+032.9641E+032.9789E+032.9556E+032.9881E+032.9586E+032.8866E+032.8426E+032.9910E+03
Avg2.8743E+033.0319E+033.0230E+033.0026E+033.0032E+033.0054E+032.9276E+032.8731E+033.0036E+03
Std3.4835E+013.7227E+012.7036E+011.7061E+018.9701E+002.2054E+012.0355E+011.8963E+018.5315E+00
Rank298457316
F24Best2.8755E+032.9742E+032.8980E+032.8876E+032.8878E+033.0226E+032.9078E+032.8944E+032.8882E+03
Avg2.8831E+033.0436E+032.9508E+032.8890E+032.8888E+033.0740E+032.9496E+032.9086E+032.8909E+03
Std1.6523E+014.8366E+012.4169E+012.1380E+007.2341E-014.5806E+012.9317E+011.0150E+012.7301E+00
Rank187329654
F25Best3.5533E+033.8738E+033.1771E+035.2000E+035.1425E+034.3885E+034.4044E+033.7982E+032.9376E+03
Avg3.9352E+035.4866E+035.1380E+035.3909E+035.3555E+035.5710E+034.9261E+034.0743E+035.0642E+03
Std2.2284E+026.8761E+028.4248E+021.0067E+021.1908E+023.6806E+023.1798E+021.3371E+028.7128E+02
Rank185769324
F26Best3.1264E+033.2424E+033.2228E+033.2167E+033.2197E+033.2827E+033.2199E+033.1986E+033.2203E+03
Avg3.1792E+033.2904E+033.2407E+033.2276E+033.2260E+033.3196E+033.2454E+033.2173E+033.2275E+03
Std1.8144E+014.4358E+011.2849E+017.9249E+004.9678E+002.7690E+011.6747E+011.0196E+017.7115E+00
Rank186539724
F27Best3.1000E+033.3173E+033.2940E+033.2298E+033.2246E+033.3488E+033.2542E+033.2694E+033.2303E+03
Avg3.1320E+033.4898E+033.3290E+033.2492E+033.2411E+033.4541E+033.3427E+033.2939E+033.2548E+03
Std5.6754E+019.1542E+012.4677E+011.5023E+011.4772E+017.4654E+015.3891E+011.4964E+012.3270E+01
Rank196328754
F28Best3.3836E+034.1280E+033.6505E+033.8266E+033.8807E+033.8818E+033.5660E+033.3980E+033.9226E+03
Avg3.5263E+034.4271E+034.1402E+034.0886E+034.0728E+034.1646E+033.9638E+033.6807E+034.0994E+03
Std9.7478E+011.9062E+022.1169E+021.1789E+021.0271E+021.4150E+022.3204E+021.9090E+021.3534E+02
Rank197548326
F29Best3.4105E+031.6772E+051.4034E+051.0620E+042.4450E+042.2141E+062.2512E+057.0122E+031.3130E+05
Avg3.7782E+031.4152E+067.0488E+052.0982E+044.3317E+045.2108E+063.3277E+061.3570E+042.9383E+05
Std3.7754E+021.2694E+065.1166E+057.3986E+031.1628E+042.5394E+062.1015E+065.9159E+031.4545E+05
Rank176349825
Table A15. Experiments comparing EECO with other competing algorithms (50D).
Table A15. Experiments comparing EECO with other competing algorithms (50D).
No.IndexEECOEDECOISGTOAAPSM-jSOLSHADE-SPACMAEOSMAGLSRIMEEPSCAESLPSO
F1Best1.0000E+024.7925E+095.0198E+085.9074E+061.0837E+076.7255E+094.2879E+081.0000E+028.5347E+07
Avg1.0000E+029.5729E+091.0159E+091.3639E+071.3365E+071.0492E+101.1763E+098.3811E+081.0300E+08
Std7.6907E-073.5920E+094.1380E+085.3520E+062.2389E+062.0903E+094.8071E+088.4241E+081.1330E+07
Rank186329754
F2Best3.0000E+025.4017E+048.6516E+041.4551E+041.9793E+049.9104E+046.9286E+046.7978E+021.0575E+05
Avg3.0000E+027.0252E+041.2344E+052.2523E+045.2198E+041.5120E+051.2072E+051.6096E+051.5294E+05
Std1.9107E-081.3026E+041.8316E+045.0574E+033.1839E+042.9818E+042.4896E+049.2576E+042.1898E+04
Rank146237598
F3Best4.0000E+021.1518E+036.8489E+025.2103E+025.9828E+021.3513E+037.4444E+025.1495E+025.5752E+02
Avg4.0133E+021.7277E+037.7378E+026.1496E+026.2381E+021.7678E+038.3701E+027.0252E+026.2271E+02
Std1.9453E+005.2206E+026.6121E+013.1321E+018.9771E+003.9025E+026.3582E+011.0857E+023.0933E+01
Rank186249753
F4Best5.4079E+028.3901E+028.4461E+028.3498E+028.3647E+028.2578E+027.0069E+025.5373E+028.5124E+02
Avg5.6799E+029.3781E+029.3004E+028.6507E+028.7054E+028.9102E+027.9503E+026.4899E+028.7443E+02
Std2.3514E+015.1851E+014.1489E+011.3790E+011.4011E+013.7282E+015.5267E+015.0249E+011.4224E+01
Rank198457326
F5Best6.0322E+026.3535E+026.2021E+026.0167E+026.0249E+026.2630E+026.1959E+026.0367E+026.0427E+02
Avg6.0774E+026.4746E+026.2956E+026.0247E+026.0299E+026.3572E+026.3278E+026.0949E+026.0561E+02
Std3.3724E+007.6751E+005.5514E+003.8990E-012.2534E-016.1215E+001.1901E+013.5863E+005.0561E-01
Rank496128753
F6Best7.7267E+021.2171E+031.2151E+031.0815E+031.0811E+031.2471E+031.1150E+038.5295E+021.1103E+03
Avg8.4986E+021.4130E+031.2554E+031.1177E+031.1159E+031.3265E+031.2532E+039.8090E+021.1334E+03
Std4.2473E+011.0399E+022.4850E+011.6135E+011.9252E+015.0049E+017.8812E+015.4072E+011.5136E+01
Rank197438625
F7Best8.3582E+021.1011E+031.1710E+031.1249E+031.1405E+031.1430E+031.0207E+038.6467E+021.1534E+03
Avg8.7429E+021.2006E+031.2343E+031.1637E+031.1679E+031.1996E+031.1008E+039.5560E+021.1719E+03
Std1.6703E+015.3187E+013.1891E+011.5381E+011.5001E+013.3559E+014.0847E+017.3620E+011.0452E+01
Rank189457326
F8Best1.1323E+037.5727E+034.0409E+039.1082E+029.2766E+025.3319E+034.9679E+031.3227E+039.9687E+02
Avg1.4867E+031.3514E+047.3077E+039.3337E+029.3897E+028.3575E+039.9996E+031.8565E+031.0387E+03
Std2.6421E+023.4502E+031.7918E+031.3786E+017.1343E+002.1976E+033.9272E+035.1287E+022.4307E+01
Rank496127853
F9Best2.5378E+031.0920E+041.2725E+041.3719E+041.4265E+041.2941E+048.1320E+035.6998E+031.4106E+04
Avg7.0564E+031.2972E+041.4412E+041.5023E+041.4966E+041.4260E+049.7476E+037.9829E+031.4832E+04
Std1.7152E+039.5550E+028.1708E+024.5179E+023.6655E+024.8781E+029.4268E+021.3014E+032.8587E+02
Rank146985327
F10Best1.1726E+031.9963E+034.1271E+031.3163E+031.3650E+034.7506E+031.7751E+031.3326E+031.4419E+03
Avg1.2313E+032.4568E+036.1314E+031.3782E+031.4169E+035.4949E+032.0200E+032.2524E+031.5925E+03
Std3.7132E+013.0428E+021.2820E+034.8200E+013.4489E+016.4461E+021.6925E+029.9187E+028.0581E+01
Rank179238564
F11Best2.1612E+031.8362E+081.9031E+072.3705E+064.6020E+063.8819E+081.0328E+089.9226E+052.1062E+07
Avg3.6113E+034.2147E+086.3942E+077.7817E+066.9384E+066.3808E+082.9363E+083.1844E+073.2462E+07
Std7.8086E+021.4560E+082.2229E+074.7176E+061.9812E+062.5986E+081.8555E+082.8985E+079.3116E+06
Rank186329745
F12Best2.0979E+039.9271E+052.0001E+055.0219E+043.2898E+058.5759E+066.4451E+052.2504E+033.8586E+05
Avg3.1305E+033.9607E+065.7247E+057.4997E+045.8056E+054.3484E+075.0799E+063.9705E+049.6383E+05
Std6.7394E+022.2097E+063.6294E+051.7410E+041.8887E+052.1749E+072.9461E+063.2215E+045.2587E+05
Rank174359826
F13Best1.5016E+035.6567E+031.2889E+051.7467E+033.5658E+039.0907E+041.2677E+053.4101E+048.0263E+03
Avg1.6079E+033.7291E+045.0575E+051.8468E+035.3096E+033.7901E+055.6832E+056.1092E+051.9104E+04
Std1.0883E+024.1427E+043.4244E+056.7422E+011.0260E+031.7963E+054.1996E+058.0036E+051.6517E+04
Rank157236894
F14Best1.6537E+034.6546E+043.7992E+046.9041E+036.8470E+041.9335E+062.2232E+051.9914E+038.2942E+04
Avg1.8610E+031.3694E+056.6119E+041.6564E+041.2449E+055.0691E+061.1459E+067.3151E+032.3992E+05
Std1.0930E+026.4251E+042.0375E+044.9806E+034.3488E+043.1616E+067.3247E+057.1341E+031.5834E+05
Rank164359827
F15Best1.7283E+033.3842E+033.6473E+034.2071E+034.1188E+033.8098E+032.8629E+032.5407E+034.3911E+03
Avg2.0247E+034.2565E+034.7004E+034.6614E+034.6935E+034.4357E+033.4765E+033.0336E+034.8548E+03
Std1.9968E+024.1388E+024.9963E+022.3479E+022.6088E+023.4461E+024.4703E+024.1882E+022.2153E+02
Rank148675329
F16Best1.8389E+033.4535E+033.1547E+033.1146E+033.4285E+032.9547E+032.7750E+032.3718E+033.3046E+03
Avg2.0337E+033.7373E+033.6677E+033.7161E+033.7281E+033.4975E+033.3136E+032.9548E+033.7265E+03
Std1.1829E+021.8860E+023.5955E+022.1162E+021.5927E+022.5763E+022.8519E+022.6549E+022.1161E+02
Rank195684327
F17Best1.8903E+031.0738E+051.4278E+061.2394E+044.5180E+041.8088E+063.5447E+055.1708E+051.7988E+05
Avg2.0273E+034.5207E+053.9660E+062.4129E+047.0902E+043.6671E+065.6955E+063.0804E+063.0443E+05
Std9.8536E+012.8309E+052.0673E+067.6372E+031.4120E+041.7237E+066.2002E+063.4610E+061.3577E+05
Rank158237964
F18Best1.9845E+032.3113E+045.9957E+047.3891E+033.5872E+045.2394E+051.9849E+052.1223E+031.0013E+05
Avg2.0477E+031.8981E+051.7458E+051.2745E+045.4590E+043.0907E+063.5353E+061.4093E+041.9283E+05
Std5.2258E+011.5998E+051.2487E+054.2891E+031.3250E+041.8501E+064.0876E+061.0908E+041.2818E+05
Rank165248937
F19Best2.0485E+032.8216E+033.7080E+033.4971E+033.2913E+033.3173E+032.8268E+032.4750E+033.6671E+03
Avg2.1193E+033.5595E+033.9565E+033.9543E+033.8949E+033.6939E+033.0847E+033.0751E+033.9739E+03
Std5.4049E+012.8791E+021.7104E+022.0482E+022.3720E+022.1436E+022.2873E+023.5762E+021.8028E+02
Rank148765329
F20Best2.3290E+032.5843E+032.6638E+032.5943E+032.6313E+032.6240E+032.5407E+032.3668E+032.6548E+03
Avg2.3575E+032.7046E+032.7323E+032.6657E+032.6709E+032.6851E+032.5873E+032.4609E+032.6797E+03
Std1.4863E+015.7673E+012.4706E+012.2249E+011.8941E+012.9941E+013.3609E+016.4711E+011.2923E+01
Rank189457326
F21Best2.3046E+031.2373E+041.5197E+042.7784E+031.4386E+044.9149E+039.3960E+037.9801E+031.5814E+04
Avg7.8366E+031.4490E+041.6522E+041.5718E+041.5978E+041.3243E+041.0749E+049.6922E+031.6400E+04
Std2.9475E+039.3920E+025.2400E+023.5991E+037.6138E+024.5054E+038.3400E+021.0018E+032.9268E+02
Rank159674328
F22Best2.7553E+033.1573E+033.0897E+033.0833E+033.0528E+033.1440E+033.0060E+032.8151E+033.0752E+03
Avg2.8522E+033.2315E+033.1659E+033.1027E+033.0968E+033.1808E+033.0702E+032.9004E+033.1079E+03
Std6.4461E+016.2271E+014.3980E+011.2164E+011.7536E+012.8850E+015.6650E+014.1724E+011.4814E+01
Rank197548326
F23Best2.9611E+033.2354E+033.3081E+033.2334E+033.2251E+033.2558E+033.0903E+032.9768E+033.2238E+03
Avg3.0461E+033.3423E+033.3377E+033.2658E+033.2550E+033.3009E+033.2048E+033.0482E+033.2629E+03
Std6.4960E+016.7906E+011.9794E+011.7941E+011.6958E+012.9647E+015.3517E+013.7894E+011.9413E+01
Rank198647325
F24Best2.9312E+033.5671E+033.1888E+033.0350E+033.0418E+033.7865E+033.2044E+033.0687E+033.0678E+03
Avg2.9720E+033.8731E+033.3337E+033.0859E+033.0501E+034.1261E+033.4075E+033.1902E+033.1000E+03
Std2.2055E+012.2550E+029.8461E+012.4401E+014.3327E+002.2517E+022.0445E+029.3950E+012.0350E+01
Rank186329754
F25Best2.9000E+037.8482E+037.3357E+036.8484E+036.9900E+037.8161E+036.5302E+034.7513E+037.0961E+03
Avg4.9613E+038.8606E+038.1295E+037.2052E+037.2100E+038.2728E+037.2049E+035.3230E+037.3853E+03
Std7.5099E+027.6881E+024.5846E+021.8946E+021.4696E+023.1546E+026.4412E+024.1034E+021.3376E+02
Rank197458326
F26Best3.1532E+033.5674E+033.4093E+033.2732E+033.2575E+033.7077E+033.4227E+033.3322E+033.2747E+03
Avg3.2543E+033.7453E+033.5588E+033.3294E+033.2890E+033.8844E+033.5860E+033.4475E+033.3690E+03
Std1.3207E+021.6783E+021.0584E+024.0700E+012.4961E+018.7655E+018.7932E+017.6648E+015.0872E+01
Rank186329754
F27Best3.2635E+033.8428E+033.5801E+033.3234E+033.2985E+034.3417E+033.4905E+033.3152E+033.3572E+03
Avg3.2976E+034.7429E+033.7356E+033.3514E+033.3233E+034.8269E+033.8602E+033.6566E+033.3873E+03
Std9.4362E+004.8091E+021.0505E+021.8705E+011.3083E+013.0065E+023.3498E+022.9360E+022.8164E+01
Rank186329754
F28Best3.2211E+034.9510E+034.2507E+034.7490E+034.7655E+034.8872E+034.6196E+033.8950E+034.6079E+03
Avg3.4463E+035.9246E+035.1588E+034.9660E+034.9498E+035.4116E+034.9670E+034.2825E+035.0258E+03
Std1.4832E+026.0421E+025.5983E+021.4004E+029.5998E+012.5365E+023.1217E+023.6965E+022.2539E+02
Rank197438526
F29Best3.4159E+032.6903E+072.0703E+073.0284E+063.6764E+069.8686E+075.2163E+078.1890E+051.1798E+07
Avg4.3805E+034.7821E+073.0285E+074.3502E+064.4486E+061.4598E+089.8333E+072.6875E+061.8853E+07
Std9.9589E+021.7872E+077.1760E+061.1703E+065.8131E+053.5820E+073.8102E+071.1125E+066.8320E+06
Rank176349825
Table A16. Experiments comparing EECO with other competing algorithms (100D).
Table A16. Experiments comparing EECO with other competing algorithms (100D).
No.IndexEECOEDECOISGTOAAPSM-jSOLSHADE-SPACMAEOSMAGLSRIMEEPSCAESLPSO
F1Best1.0000E+024.8379E+101.3587E+103.1413E+081.1784E+084.8564E+101.9190E+107.1108E+051.3047E+09
Avg2.0403E+026.1811E+101.8451E+105.3099E+081.2473E+085.7195E+102.4351E+107.4247E+091.5611E+09
Std2.3260E+021.8831E+104.5820E+091.9969E+089.6664E+065.9532E+093.7010E+091.0261E+102.7030E+08
Rank196328754
F2Best3.0018E+021.5782E+052.6064E+058.9129E+043.0264E+053.2370E+053.7860E+058.2013E+023.0151E+05
Avg3.0082E+021.8220E+052.9572E+059.9055E+043.5234E+053.9258E+054.4916E+052.9782E+053.8888E+05
Std4.5854E-013.1844E+042.5915E+041.0635E+044.5239E+046.4069E+046.3161E+042.9233E+055.7859E+04
Rank134268957
F3Best4.0000E+024.2224E+032.0489E+038.5845E+027.2758E+025.4389E+032.7096E+037.2996E+021.0277E+03
Avg4.0319E+026.9339E+032.3820E+039.0933E+027.4853E+027.3769E+033.1728E+031.2903E+031.0918E+03
Std1.7829E+002.6087E+032.0093E+023.7777E+011.7741E+011.7635E+033.4369E+027.5332E+025.7149E+01
Rank186329754
F4Best6.7511E+021.5015E+031.4864E+031.2944E+031.2912E+031.3964E+031.3612E+039.9549E+021.3178E+03
Avg7.1033E+021.6051E+031.6202E+031.3281E+031.3186E+031.4738E+031.4419E+031.1009E+031.3766E+03
Std3.4856E+016.6516E+017.9081E+011.9652E+012.3920E+016.8810E+016.3334E+011.0250E+023.5681E+01
Rank189437625
F5Best6.1293E+026.6694E+026.4787E+026.0590E+026.0413E+026.5171E+026.4725E+026.1792E+026.1095E+02
Avg6.1435E+026.7373E+026.5577E+026.0704E+026.0465E+026.5622E+026.7081E+026.2358E+026.1184E+02
Std1.1095E+007.4344E+004.9464E+008.6795E-013.5732E-012.6448E+001.6396E+015.4963E+005.9642E-01
Rank496217853
F6Best9.7962E+022.6367E+032.0705E+031.6167E+031.6070E+032.3544E+032.3087E+031.6258E+031.7068E+03
Avg1.1300E+032.8628E+032.2378E+031.6528E+031.6303E+032.5699E+032.4029E+031.8299E+031.7299E+03
Std1.8465E+021.5072E+021.1641E+022.5044E+012.1430E+011.4196E+028.8462E+011.5337E+022.2737E+01
Rank196328754
F7Best9.9203E+021.8884E+031.8376E+031.6226E+031.5913E+031.7625E+031.5804E+031.0066E+031.6344E+03
Avg1.0784E+031.9869E+031.9361E+031.6561E+031.6129E+031.8331E+031.7335E+031.1637E+031.6832E+03
Std6.6466E+019.0131E+015.8657E+012.2275E+011.8455E+016.6286E+019.8631E+011.8091E+023.2922E+01
Rank198437625
F8Best3.4202E+034.0886E+043.4414E+041.4879E+031.0764E+033.1307E+043.8552E+047.8049E+032.2476E+03
Avg3.8428E+034.4753E+043.8439E+041.7385E+031.1256E+033.5944E+044.9874E+041.1314E+042.8805E+03
Std4.2226E+023.2750E+034.6160E+032.2207E+024.6227E+013.4154E+031.1665E+043.2000E+035.2043E+02
Rank487216953
F9Best1.5353E+042.7140E+043.1479E+043.1038E+043.1784E+042.9967E+042.2370E+041.2564E+043.1010E+04
Avg1.6276E+042.8948E+043.1646E+043.1683E+043.2057E+043.0463E+042.3453E+041.8019E+043.2042E+04
Std9.8458E+021.1696E+032.0815E+025.2469E+022.5004E+026.6445E+026.7190E+024.0257E+036.4395E+02
Rank146795328
F10Best1.8790E+032.3193E+047.6848E+042.9050E+034.3742E+035.3742E+042.7795E+042.4983E+036.4047E+03
Avg2.0621E+032.7056E+048.8803E+043.4129E+035.1767E+039.2718E+044.1006E+042.0006E+049.3371E+03
Std1.8346E+026.5231E+031.1878E+044.1779E+028.0118E+022.5721E+041.3080E+041.8045E+042.6675E+03
Rank168239754
F11Best7.9353E+034.0450E+099.7195E+081.0456E+088.1819E+077.2926E+091.6969E+092.5597E+073.3007E+08
Avg1.5437E+045.5766E+091.1646E+091.2189E+081.0070E+088.5510E+092.9794E+095.1945E+084.2023E+08
Std6.0307E+031.6371E+092.3091E+081.8941E+071.7360E+071.8395E+098.4621E+086.7182E+088.4358E+07
Rank186329754
F12Best4.7620E+033.5249E+073.4480E+068.9341E+049.8458E+051.9712E+083.0338E+076.5771E+033.8267E+06
Avg5.5317E+031.1336E+084.3873E+061.0032E+051.2322E+063.0777E+086.4860E+071.2807E+064.8913E+06
Std8.7238E+025.8478E+075.5463E+051.1581E+042.0781E+058.2320E+072.0994E+071.2290E+068.6906E+05
Rank185239746
F13Best1.6439E+032.2525E+054.6082E+062.3156E+049.4020E+044.2325E+062.3796E+062.0997E+052.3300E+05
Avg1.7949E+033.4803E+057.2496E+063.0468E+041.3385E+056.0535E+068.3617E+062.2359E+063.7233E+05
Std1.3081E+021.1378E+053.0887E+067.2471E+032.4750E+041.7004E+065.8516E+061.8871E+069.9123E+04
Rank148237965
F14Best1.6862E+031.1581E+062.0658E+054.4076E+043.8872E+051.6547E+077.4203E+062.2706E+036.8248E+05
Avg1.8197E+033.3236E+063.5489E+055.0764E+044.9814E+053.3258E+079.4527E+062.2553E+048.3808E+05
Std1.3665E+021.8988E+061.7746E+056.3644E+031.1286E+051.4796E+071.6281E+061.9145E+041.5439E+05
Rank174359826
F15Best2.3393E+037.9519E+037.9858E+039.1881E+038.9628E+037.3275E+036.3181E+034.7992E+039.5017E+03
Avg3.0949E+038.8414E+039.5648E+039.6219E+039.5800E+038.7502E+037.2218E+035.3769E+039.6866E+03
Std8.1751E+027.5517E+021.2259E+032.5685E+024.0997E+021.0843E+036.8335E+025.0690E+022.0314E+02
Rank156874329
F16Best1.9698E+034.6715E+035.9715E+036.7170E+036.3172E+036.4655E+035.6248E+033.9034E+036.5312E+03
Avg2.4605E+036.2705E+037.0811E+037.0130E+036.7541E+036.6535E+035.9590E+034.7150E+037.0159E+03
Std4.3992E+029.3236E+026.6807E+021.7051E+022.4617E+021.3840E+024.2303E+021.2374E+033.0398E+02
Rank149765328
F17Best1.9604E+032.6923E+054.4372E+067.5469E+041.8963E+055.0657E+061.1563E+073.8964E+055.8576E+05
Avg2.0826E+037.8960E+057.1941E+069.8189E+042.7589E+058.6633E+061.4854E+073.1946E+068.2113E+05
Std7.2829E+014.0146E+052.4483E+061.5079E+047.4585E+042.2780E+062.6954E+064.1243E+062.0723E+05
Rank147238965
F18Best2.1820E+036.2172E+061.7909E+062.4678E+057.6834E+051.1497E+072.5653E+072.4024E+038.0797E+05
Avg2.2686E+031.7037E+073.2919E+062.9100E+058.5443E+054.0115E+073.7473E+071.1773E+051.2398E+06
Std1.4156E+029.9133E+061.5461E+065.9895E+049.6137E+041.7362E+071.2156E+071.3239E+053.3106E+05
Rank176349825
F19Best2.4218E+035.8890E+036.2083E+037.1130E+037.1780E+036.7053E+034.9963E+034.3177E+037.2462E+03
Avg2.9438E+036.3470E+037.1617E+037.3074E+037.3910E+037.0502E+035.6282E+034.6207E+037.3965E+03
Std9.2056E+023.7851E+025.3768E+022.2998E+021.4397E+022.5093E+024.8177E+023.2189E+021.7397E+02
Rank146785329
F20Best2.4965E+033.3679E+033.3347E+033.1707E+033.1223E+033.3071E+033.1379E+032.7885E+033.1600E+03
Avg2.5726E+033.4540E+033.4234E+033.1876E+033.1469E+033.3611E+033.2538E+032.8700E+033.1953E+03
Std5.2607E+016.0940E+017.9293E+011.2574E+011.7170E+014.6798E+011.0207E+025.5279E+013.1818E+01
Rank198437625
F21Best8.4600E+032.9367E+043.2994E+043.3590E+043.3766E+043.1976E+042.3169E+041.5031E+043.3065E+04
Avg1.2134E+042.9878E+043.3717E+043.4111E+043.4417E+043.2772E+042.5671E+041.9508E+043.3938E+04
Std4.7472E+034.4173E+025.9534E+025.7917E+024.7144E+025.3976E+021.8707E+033.4046E+037.3430E+02
Rank146895327
F22Best3.0687E+034.0653E+033.9400E+033.6925E+033.6493E+033.9033E+033.7359E+033.3139E+033.6922E+03
Avg3.2777E+034.1762E+033.9789E+033.7091E+033.6894E+033.9989E+033.8429E+033.3942E+033.7510E+03
Std2.3454E+028.0793E+014.5017E+012.2184E+012.3338E+017.3385E+017.4340E+011.0166E+024.6763E+01
Rank197438625
F23Best3.6738E+034.6981E+034.4260E+034.0759E+034.0977E+034.5645E+034.1381E+033.5711E+034.1660E+03
Avg4.0880E+034.8790E+034.5490E+034.1261E+034.1159E+034.7293E+034.3823E+033.7734E+034.1818E+03
Std3.1774E+021.4722E+028.3143E+013.6417E+011.4013E+011.5559E+021.7018E+022.0642E+021.7365E+01
Rank297438615
F24Best3.1967E+036.3159E+034.6170E+033.5538E+033.5144E+037.8948E+034.7439E+033.4938E+033.7366E+03
Avg3.2189E+037.7250E+034.9164E+033.6117E+033.5331E+038.6365E+035.6459E+034.5048E+033.8037E+03
Std2.2558E+011.1846E+033.7935E+025.1638E+011.5957E+019.6079E+025.3655E+029.0755E+026.1218E+01
Rank186329754
F25Best1.0890E+041.8456E+041.7562E+041.3904E+041.3626E+041.8606E+041.6670E+048.5862E+031.4546E+04
Avg1.3891E+042.1812E+041.8696E+041.4065E+041.4080E+041.9875E+041.8977E+041.0929E+041.4657E+04
Std2.1456E+033.7240E+037.2192E+021.6573E+022.9501E+021.4324E+032.0657E+031.9896E+038.6922E+01
Rank296348715
F26Best3.2000E+033.9018E+033.8074E+033.4116E+033.3994E+034.5302E+033.8809E+033.5287E+033.6936E+03
Avg3.6020E+034.1419E+033.9447E+033.4738E+033.4136E+034.6310E+033.9918E+033.6946E+033.7406E+03
Std2.9031E+021.8102E+021.0736E+025.6774E+011.2143E+019.4729E+011.0460E+021.6294E+024.3592E+01
Rank386219745
F27Best3.2718E+038.0033E+035.8814E+033.7345E+033.5343E+039.9385E+037.5866E+033.5610E+034.0074E+03
Avg3.2993E+038.9719E+036.3603E+033.7875E+033.5610E+031.0738E+049.0128E+035.0413E+034.1158E+03
Std2.6190E+017.3870E+024.2891E+025.6185E+011.9434E+015.5354E+021.5028E+031.9962E+037.5592E+01
Rank176329854
F28Best4.0991E+031.0137E+049.1411E+038.9116E+038.5558E+039.6930E+038.9844E+036.5009E+038.7843E+03
Avg4.7295E+031.1625E+049.8342E+039.1304E+038.8456E+031.0337E+049.8153E+036.9787E+039.3713E+03
Std4.2458E+021.1352E+036.0825E+021.6976E+022.4390E+024.7938E+026.6407E+024.5606E+025.2611E+02
Rank197438625
F29Best4.6070E+038.1812E+071.0910E+071.9050E+062.4676E+062.3263E+082.1026E+083.2257E+047.4875E+06
Avg7.1070E+031.5251E+084.4490E+073.0496E+063.4087E+063.1959E+083.0248E+083.0475E+068.4412E+06
Std2.4952E+034.4907E+072.8090E+071.3875E+066.1816E+059.9881E+077.4762E+074.0098E+066.7657E+05
Rank176349825

References

  1. Lehmann, T.H. Mathematical Modelling as a Vehicle for Eliciting Algorithmic Thinking. Educ. Stud. Math. 2024, 115, 151–176. [Google Scholar] [CrossRef]
  2. Tang, A.D.; Tang, S.Q.; Han, T.; Zhou, H.; Xie, L. A Modified Slime Mould Algorithm for Global Optimization. Comput. Intell. Neurosci. 2021, 2021, 2298215. [Google Scholar] [CrossRef]
  3. Liu, Y.; As’arry, A.; Hassan, M.K.; Hairuddin, A.A.; Mohamad, H. Review of the Grey Wolf Optimization Algorithm: Variants and Applications. Neural Comput. Appl. 2024, 36, 2713–2735. [Google Scholar] [CrossRef]
  4. Dey, B.; Sharma, G.; Bokoro, P.N. A Novel Hybrid Crow Search Arithmetic Optimization Algorithm for Solving Weighted Combined Economic Emission Dispatch with Load-Shifting Practice. Algorithms 2024, 17, 313. [Google Scholar] [CrossRef]
  5. Keshta, H.E.; Malik, O.P.; Saied, E.M.; Bendary, F.M.; Ali, A.A. Energy Management System for Two Islanded Interconnected Micro-Grids Using Advanced Evolutionary Algorithms. Electr. Power Syst. Res. 2021, 192, 106958. [Google Scholar] [CrossRef]
  6. Tan, M.; Tang, A.; Ding, D.; Xie, L.; Huang, C. Autonomous Air Combat Maneuvering Decision Method of UCAV Based on LSHADE-TSO-MPC under Enemy Trajectory Prediction. Electronics 2022, 11, 3383. [Google Scholar] [CrossRef]
  7. Tang, A.D.; Han, T.; Zhou, H.; Xie, L. An Improved Equilibrium Optimizer with Application in Unmanned Aerial Vehicle Path Planning. Sensors 2021, 21, 1814. [Google Scholar] [CrossRef]
  8. Zhou, H.; Cheng, H.Y.; Wei, Z.L.; Zhao, X.; Tang, A.D.; Xie, L. A Hybrid Butterfly Optimization Algorithm for Numerical Optimization Problems. Comput. Intell. Neurosci. 2021, 2021, 7981670. [Google Scholar] [CrossRef]
  9. Cui, L.L.; Hu, G.; Zhu, Y.L. Multi-Strategy Improved Snow Ablation Optimizer: A Case Study of Optimization of Kernel Extreme Learning Machine for Flood Prediction. Artif. Intell. Rev. 2025, 58, 181. [Google Scholar] [CrossRef]
  10. Xie, L.; Wei, Z.; Ding, D.; Zhang, Z.; Tang, A. Long and Short Term Maneuver Trajectory Prediction of UCAV Based on Deep Learning. IEEE Access 2021, 9, 32321–32340. [Google Scholar] [CrossRef]
  11. Shi, J.E.; Chen, Y.; Cai, Z.N.; Heidari, A.A.; Chen, H.L.; He, Q.X. Multi-Threshold Image Segmentation Using a Boosted Whale Optimization: Case Study of Breast Invasive Ductal Carcinomas. Clust. Comput. 2024, 27, 14891–14949. [Google Scholar] [CrossRef]
  12. Fan, Q.; Ma, Y.; Wang, P.; Bai, F. Otsu Image Segmentation Based on a Fractional Order Moth–Flame Optimization Algorithm. Fractal Fract. 2024, 8, 87. [Google Scholar] [CrossRef]
  13. Yang, J.; Xia, Y. Coverage and Routing Optimization of Wireless Sensor Networks Using Improved Cuckoo Algorithm. IEEE Access 2024, 12, 39564–39577. [Google Scholar] [CrossRef]
  14. Song, J.; Hu, Y.M.; Luo, Y.B. Wireless Sensor Network Coverage Optimization Based on the Novel Enhanced Hunter-Prey Optimization Algorithm. IEEE Sens. J. 2024, 24, 31172–31187. [Google Scholar] [CrossRef]
  15. Tang, A.; Zhou, H.; Han, T.; Xie, L. A Modified Manta Ray Foraging Optimization for Global Optimization Problems. IEEE Access 2021, 9, 128702–128721. [Google Scholar] [CrossRef]
  16. Tang, A.; Zhou, H.; Han, T.; Xie, L. A Chaos Sparrow Search Algorithm with Logarithmic Spiral and Adaptive Step for Engineering Problems. Comput. Model. Eng. Sci. 2022, 130, 331–364. [Google Scholar] [CrossRef]
  17. Prity, F.S.; Gazi, M.H.; Uddin, K.M.A. A Review of Task Scheduling in Cloud Computing Based on Nature-Inspired Optimization Algorithm. Clust. Comput. 2023, 26, 3037–3067. [Google Scholar] [CrossRef]
  18. Luo, Z.Y.; Chen, Y.N.; Liu, X.T. Research on Sparrow Search Optimization Algorithm for Multi-Objective Task Scheduling in Cloud Computing Environment. J. Intell. Fuzzy Syst. 2023, 45, 10397–10409. [Google Scholar] [CrossRef]
  19. Khan, M.S.A.; Santhosh, R. Task Scheduling in Cloud Computing Using Hybrid Optimization Algorithm. Soft Comput. 2022, 26, 13069–13079. [Google Scholar] [CrossRef]
  20. Czarnul, P.; Antal, M.; Baniata, H.; Griebler, D.; Kertesz, A.; Kessler, C.W.; Kouloumpris, A.; Kovacic, S.; Markus, A.; Michael, M.K.; et al. Optimization of Resource-Aware Parallel and Distributed Computing: A Review. J. Supercomput. 2025, 81, 848. [Google Scholar] [CrossRef]
  21. Zhou, Z.L.; Xia, Y.; Yu, S.; Hu, J.Y.; Wang, L.M.; Hou, R.X. Optimization Calculating of Artificial Intelligence IPGA Algorithm. Int. J. Pattern Recognit. Artif. Intell. 2025, 39, 2559009. [Google Scholar] [CrossRef]
  22. Mabadifar, T.; Attarzadeh, I.; Mahdipour, E. The Improvement of the Distributed Computing Efficiency in Cloud-Fog Environments Using Data Mining and Metaheuristic Algorithms. J. Supercomput. 2025, 81, 506. [Google Scholar] [CrossRef]
  23. Xie, L.; Han, T.; Zhou, H.; Zhang, Z.-R.; Han, B.; Tang, A. Tuna Swarm Optimization: A Novel Swarm-Based Metaheuristic Algorithm for Global Optimization. Comput. Intell. Neurosci. 2021, 2021, 9210050. [Google Scholar] [CrossRef] [PubMed]
  24. Holland, J.H. Genetic Algorithms. Sci. Am. 1992, 267, 66–72. [Google Scholar] [CrossRef]
  25. Opara, K.R.; Arabas, J. Differential Evolution: A Survey of Theoretical Analyses. Swarm Evol. Comput. 2019, 44, 546–558. [Google Scholar] [CrossRef]
  26. Beyer, H.-G.; Schwefel, H.-P. Evolution Strategies—A Comprehensive Introduction. Nat. Comput. 2002, 1, 3–52. [Google Scholar] [CrossRef]
  27. Huang, W.; Xu, J. Particle Swarm Optimization. In Optimized Engineering Vibration Isolation, Absorption and Control; Springer Tracts in Civil Engineering; Springer: Berlin/Heidelberg, Germany, 2023. [Google Scholar]
  28. Dorigo, M.; Di Caro, G. Ant Colony Optimization: A New Meta-Heuristic. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406), Washington, DC, USA, 6–9 July 1999. [Google Scholar]
  29. Braik, M.; Al-Hiary, H. Rüppell’s Fox Optimizer: A Novel Meta-Heuristic Approach for Solving Global Optimization Problems. Clust. Comput. 2025, 28, 292. [Google Scholar] [CrossRef]
  30. El-kenawy, E.S.M.; Khodadadi, N.; Mirjalili, S.; Abdelhamid, A.A.; Eid, M.M.; Ibrahim, A. Greylag Goose Optimization: Nature-Inspired Optimization Algorithm. Expert Syst. Appl. 2024, 238, 122147. [Google Scholar] [CrossRef]
  31. Lian, J.; Hui, G.; Ma, L.; Zhu, T.; Wu, X.; Heidari, A.A.; Chen, Y.; Chen, H. Parrot Optimizer: Algorithm and Applications to Medical Problems. Comput. Biol. Med. 2024, 172, 108064. [Google Scholar] [CrossRef]
  32. Kirkpatrick, S.; Gelatt, C.D.; Vecchi, M.P. Optimization by Simulated Annealing. Science 1983, 220, 671–680. [Google Scholar] [CrossRef]
  33. He, J.H.; Zhao, S.J.; Ding, J.Y.; Wang, Y.M. Mirage Search Optimization: Application to Path Planning and Engineering Design Problems. Adv. Eng. Softw. 2025, 203, 103883. [Google Scholar] [CrossRef]
  34. Qi, A.L.; Zhao, D.; Heidari, A.A.; Liu, L.; Chen, Y.; Chen, H.L. FATA: An Efficient Optimization Method Based on Geophysics. Neurocomputing 2024, 607, 128289. [Google Scholar] [CrossRef]
  35. Yuan, C.; Zhao, D.; Heidari, A.A.; Liu, L.; Chen, Y.; Chen, H. Polar Lights Optimizer: Algorithm and Applications in Image Segmentation and Feature Selection. Neurocomputing 2024, 607, 128427. [Google Scholar] [CrossRef]
  36. Dong, Y.C.; Zhang, S.H.; Zhang, H.L.; Zhou, X.J.; Jiang, J.D. Chaotic Evolution Optimization: A Novel Metaheuristic Algorithm Inspired by Chaotic Dynamics. Chaos Solitons Fractals 2025, 192, 116049. [Google Scholar] [CrossRef]
  37. Ahmadianfar, I.; Heidari, A.A.; Noshadian, S.; Chen, H.; Gandomi, A.H. INFO: An Efficient Optimization Algorithm Based on Weighted Mean of Vectors. Expert Syst. Appl. 2022, 195, 116516. [Google Scholar] [CrossRef]
  38. Bohat, V.K.; Hashim, F.A.; Batra, H.; Abd Elaziz, M. Phototropic Growth Algorithm: A Novel Metaheuristic Inspired from Phototropic Growth of Plants. Knowl.-Based Syst. 2025, 322, 113548. [Google Scholar] [CrossRef]
  39. Wang, R.B.; Hu, R.B.; Geng, F.D.; Xu, L.; Chu, S.C.; Pan, J.S.; Meng, Z.Y.; Mirjalili, S. The Animated Oat Optimization Algorithm: A Nature-Inspired Metaheuristic for Engineering Optimization and a Case Study on Wireless Sensor Networks. Knowl.-Based Syst. 2025, 318, 113589. [Google Scholar] [CrossRef]
  40. Braik, M.; Al-Hiary, H. A Novel Meta-Heuristic Optimization Algorithm Inspired by Water Uptake and Transport in Plants. Neural Comput. Appl. 2025, 37, 13643–13724. [Google Scholar] [CrossRef]
  41. Rao, R.V.; Savsani, V.J.; Vakharia, D.P. Teaching-Learning-Based Optimization: A Novel Method for Constrained Mechanical Design Optimization Problems. CAD Comput. Aided Des. 2011, 43, 303–315. [Google Scholar] [CrossRef]
  42. Wu, X.; Li, S.B.; Jiang, X.H.; Zhou, Y.Q. Information Acquisition Optimizer: A New Efficient Algorithm for Solving Numerical and Constrained Engineering Optimization Problems. J. Supercomput. 2024, 80, 25736–25791. [Google Scholar] [CrossRef]
  43. Truong, D.N.; Chou, J.S. Metaheuristic Algorithm Inspired by Enterprise Development for Global Optimization and Structural Engineering Problems with Frequency Constraints. Eng. Struct. 2024, 318, 118679. [Google Scholar] [CrossRef]
  44. Rao, R. V Rao Algorithms: Three Metaphor-Less Simple Algorithms for Solving Optimization Problems. Int. J. Ind. Eng. Comput. 2020, 11, 107–130. [Google Scholar] [CrossRef]
  45. Rao, R.V.; Waghmare, G.G. A New Optimization Algorithm for Solving Complex Constrained Design Optimization Problems. Eng. Optim. 2017, 49, 60–83. [Google Scholar] [CrossRef]
  46. Rao, R.V.; Davim, J.P. Single, Multi-, and Many-Objective Optimization of Manufacturing Processes Using Two Novel and Efficient Algorithms with Integrated Decision-Making. J. Manuf. Mater. Process. 2025, 9, 249. [Google Scholar] [CrossRef]
  47. Lian, J.B.; Zhu, T.; Ma, L.; Wu, X.C.; Heidari, A.A.; Chen, Y.; Chen, H.L.; Hui, G.H. The Educational Competition Optimizer. Int. J. Syst. Sci. 2024, 55, 3185–3222. [Google Scholar] [CrossRef]
  48. Emam, M.M.; Abd El-Sattar, H.; Houssein, E.H.; Kamel, S. Optimized Design and Integration of an Off-Grid Solar PV-Biomass-Battery Hybrid Energy System Using an Enhanced Educational Competition Algorithm for Cost-Effective Rural Electrification. J. Energy Storage 2025, 120, 116381. [Google Scholar] [CrossRef]
  49. Tang, W.K.; Shi, S.Q.; Lu, Z.T.; Lin, M.Y.; Cheng, H. EDECO: An Enhanced Educational Competition Optimizer for Numerical Optimization Problems. Biomimetics 2025, 10, 176. [Google Scholar] [CrossRef]
  50. Tang, X.J.; Lian, J.J.; Ma, L.; Wu, X.C.; Zhong, R.; Zhang, Y.J.; Chen, H.L. IECO: An Improved Educational Competition Optimizer for State-of-the-Art Engineering Optimization. J. Big Data 2025, 12, 200. [Google Scholar] [CrossRef]
  51. Wu, G.; Mallipeddi, R.; Suganthan, P. Problem Definitions and Evaluation Criteria for the CEC 2017 Competition and Special Session on Constrained Single Objective Real-Parameter Optimization; Technical Report; Nanyang Technological University: Singapore, 2016. [Google Scholar]
  52. Rajwar, K.; Deep, K. Structural Bias in Metaheuristic Algorithms: Insights, Open Problems, and Future Prospects. Swarm Evol. Comput. 2025, 92, 101812. [Google Scholar] [CrossRef]
  53. Zhang, Y.; Chi, A. Group Teaching Optimization Algorithm with Information Sharing for Numerical Optimization and Engineering Optimization. J. Intell. Manuf. 2023, 34, 1547–1571. [Google Scholar] [CrossRef]
  54. Li, Y.; Han, T.; Zhou, H.; Wei, Y.; Wang, Y.; Tan, M.; Huang, C. APSM-JSO: A Novel JSO Variant with an Adaptive Parameter Selection Mechanism and a New External Archive Updating Mechanism. Swarm Evol. Comput. 2023, 78, 101283. [Google Scholar] [CrossRef]
  55. Mohamed, A.W.; Hadi, A.A.; Fattouh, A.M.; Jambi, K.M. LSHADE with Semi-Parameter Adaptation Hybrid with CMA-ES for Solving CEC 2017 Benchmark Problems. In Proceedings of the 2017 IEEE Congress on Evolutionary Computation (CEC), Donostia, Spain, 5–8 June 2017. [Google Scholar]
  56. Yin, S.; Luo, Q.; Zhou, Y. EOSMA: An Equilibrium Optimizer Slime Mould Algorithm for Engineering Design Problems. Arab. J. Sci. Eng. 2022, 47, 10115–10146. [Google Scholar] [CrossRef]
  57. Jia, H.; Lu, C. Guided Learning Strategy: A Novel Update Mechanism for Metaheuristic Algorithms Design and Improvement. Knowl.-Based Syst. 2024, 286, 111402. [Google Scholar] [CrossRef]
  58. Deng, L.Y.; Liu, S.Y. A Sine Cosine Algorithm Guided by Elite Pool Strategy for Global Optimization. Appl. Soft Comput. 2024, 164, 111946. [Google Scholar] [CrossRef]
  59. Deng, L.Y.; Liu, S.Y. Advancing Photovoltaic System Design: An Enhanced Social Learning Swarm Optimizer with Guaranteed Stability. Comput. Ind. 2025, 164, 104209. [Google Scholar] [CrossRef]
  60. Panigrahi, P.K.; Nayak, S. Numerical Approach to Solve Imprecisely Defined Systems Using Inner Outer Direct Search Optimization Technique. Math. Comput. Simul. 2024, 215, 578–606. [Google Scholar] [CrossRef]
  61. Zhao, S.; Wu, Y.; Tan, S.; Wu, J.; Cui, Z.; Wang, Y.G. QQLMPA: A Quasi-Opposition Learning and Q-Learning Based Marine Predators Algorithm. Expert Syst. Appl. 2023, 213, 119246. [Google Scholar] [CrossRef]
  62. Yang, X.; Zhang, L.; Qian, H.; Song, L.; Bian, J. HeurAgenix: Leveraging LLMs for Solving Complex Combinatorial Optimization Challenges. arXiv 2025, arXiv:2506.15196. [Google Scholar] [CrossRef]
  63. Panigrahi, P.K.; Nayak, S. Fuzzy Levenberg Marquart Optimization Algorithm with Inexact Line Search Technique to Solve Imprecisely Defined Nonlinear Unconstrained Optimization Problems. Int. J. Mach. Learn. Cybern. 2025, 16, 5527–5551. [Google Scholar] [CrossRef]
Figure 1. Summary of metaheuristic algorithms.
Figure 1. Summary of metaheuristic algorithms.
Biomimetics 10 00719 g001
Figure 2. A complete outline of this work.
Figure 2. A complete outline of this work.
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Figure 3. Flowchart of the EECO algorithm.
Figure 3. Flowchart of the EECO algorithm.
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Figure 4. Friedman rankings of the EECO with different population sizes.
Figure 4. Friedman rankings of the EECO with different population sizes.
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Figure 5. Friedman rankings of the EECO with different parameters a .
Figure 5. Friedman rankings of the EECO with different parameters a .
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Figure 6. Friedman rankings of EECO with different strategies.
Figure 6. Friedman rankings of EECO with different strategies.
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Figure 7. Nemenyi post hoc test of EECO with different strategies.
Figure 7. Nemenyi post hoc test of EECO with different strategies.
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Figure 8. Friedman rankings of EECO and other competing algorithms.
Figure 8. Friedman rankings of EECO and other competing algorithms.
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Figure 9. Nemenyi post hoc test of EECO and other competing algorithms.
Figure 9. Nemenyi post hoc test of EECO and other competing algorithms.
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Figure 10. Convergence curves of EECO and other competing algorithms.
Figure 10. Convergence curves of EECO and other competing algorithms.
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Figure 11. Boxplots of EECO and other competing algorithms.
Figure 11. Boxplots of EECO and other competing algorithms.
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Figure 12. Algorithm performance sorting radar chart of EECO and other competing algorithms.
Figure 12. Algorithm performance sorting radar chart of EECO and other competing algorithms.
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Table 1. Detailed description of CEC2017 test functions.
Table 1. Detailed description of CEC2017 test functions.
CategoryNo.Function NameFmin
Unimodal functionsF1Shifted and Rotated Bent Cigar Function100
F2Shifted and Rotated Zakharov Function300
Multimodal functionsF3Shifted and Rotated Rosenbrock’s Function400
F4Shifted and Rotated Rastrigin’s Function500
F5Shifted and Rotated Expanded Schaffer’s Function600
F6Shifted and Rotated Lunacek Bi_Rastrigin Function700
F7Shifted and Rotated Non-Continuous Rastrigin’s Function800
F8Shifted and Rotated Levy Function900
F9Shifted and Rotated Schwefel’s Function1000
Hybrid functionsF10Hybrid Function 1 (N = 3)1100
F11Hybrid Function 2 (N = 3)1200
F12Hybrid Function 3 (N = 3)1300
F13Hybrid Function 4 (N = 4)1400
F14Hybrid Function 5 (N = 4)1500
F15Hybrid Function 6 (N = 4)1600
F16Hybrid Function 6 (N = 5)1700
F17Hybrid Function 6 (N = 5)1800
F18Hybrid Function 6 (N = 5)1900
F19Hybrid Function 6 (N = 6)2000
Composition functionsF20Composition Function 1 (N = 3)2100
F21Composition Function 2 (N = 3)2200
F22Composition Function 3 (N = 4)2300
F23Composition Function 4 (N = 4)2400
F24Composition Function 5 (N = 5)2500
F25Composition Function 6 (N = 5)2600
F26Composition Function 7 (N = 6)2700
F27Composition Function 8 (N = 6)2800
F28Composition Function 9 (N = 3)2900
F29Composition Function 10 (N = 3)3000
Search Range: [ 100 , 100 ] D ; Dimension: 10/30/50/100
Table 2. Details of EECO variants with different strategies.
Table 2. Details of EECO variants with different strategies.
AlgorithmECO-RECO-PECO-TECO-RPECO-RTECO-PTEECO
RPSYNNYYNY
PMNYNYNYY
TDUFNNYNYYY
Table 3. Friedman test results obtained by EECO with different strategies.
Table 3. Friedman test results obtained by EECO with different strategies.
Test SuiteDimensionECOECO-RECO-PECO-TECO-RPECO-RTECO-PTEECOp-Value
CEC-2017107.4144.2074.6216.4483.2074.3793.9831.7415.80E-20
307.9314.7595.2416.6902.8283.6553.7241.1721.79E-30
507.8285.2075.5176.4833.0693.1033.5521.2413.74E-30
1007.7245.1385.7596.4143.3103.2073.3101.1385.96E-30
Mean rank7.7244.8285.2846.5093.1033.5863.6421.323N/A
Overall rank85672341N/A
Table 4. Wilcoxon rank sum test results of EECO with different strategies.
Table 4. Wilcoxon rank sum test results of EECO with different strategies.
vs. ECO
+/=/-
CEC-2017 Test Suite
10D30D50D100D
ECO-R23/6/028/1/024/5/020/9/0
ECO-P25/2/226/2/122/6/120/9/0
ECO-T12/17/023/6/021/8/017/12/0
ECO-RP24/5/028/1/026/3/024/5/0
ECO-RT21/8/027/2/028/1/024/5/0
ECO-PT22/7/028/1/028/1/026/3/0
EECO28/1/029/0/029/0/028/1/0
Table 5. Experimental result of CO.
Table 5. Experimental result of CO.
COIndexEECOECO
D = 30D = 100D = 30D = 100
c= (0, 0, …,0)Best0.0000E+000.0000E+006.6613E-160.0000E+00
Mean0.0000E+000.0000E+002.8759E-028.5974E-03
Std0.0000E+000.0000E+008.8467E-023.2676E-02
Rank1122
c= (25, 25, …, 25)Best0.0000E+000.0000E+001.2579E-015.9336E-02
Mean3.2016E-032.7909E-034.8354E-013.3116E-01
Std8.7753E-037.5325E-032.4722E-011.9795E-01
Rank1122
c= (50, 50, …, 50)Best0.0000E+000.0000E+001.3246E-028.6688E-02
Mean1.2322E-033.2029E-034.3004E-012.8875E-01
Std3.2837E-039.3339E-032.3363E-011.5740E-01
Rank1122
c= (75, 75, …, 75)Best0.0000E+000.0000E+003.7604E-036.4040E-02
Mean3.2031E-032.4632E-033.5626E-014.0825E-01
Std7.6592E-035.1712E-032.3738E-011.9091E-01
Rank1122
c= (100, 100, …, 100)Best0.0000E+000.0000E+000.0000E+000.0000E+00
Mean0.0000E+000.0000E+000.0000E+000.0000E+00
Std0.0000E+000.0000E+000.0000E+000.0000E+00
Rank1111
Table 6. Parameter settings of EECO and other algorithms.
Table 6. Parameter settings of EECO and other algorithms.
AlgorithmParameter Settings
EECO H = 0.5 , G 1 = 0.2 , G 2 = 0.1 , a = 0.8
ECO H = 0.5 , G 1 = 0.2 , G 2 = 0.1
EDECO H = 0.5 , G 1 = 0.2 , G 2 = 0.1 , α = 10 , β = 0.4
ISGTOA A r = 2 N
APSM-jSO k = 3 , F = 0.3 , c r = 0.8 , h = 6 , a = 1.3
LSHADE-SPACMA p = 0.11 , a = 1.4 , m = 5 , f = 0.5
EOSMA a 1 = 2 , a 2 = 1 , G P = 0.5 , z = 0.6 , q = 0.2
GLSRIME w = 5 , C m a x = 250 , α = 30
EPSCA a = 2 , β = 0.5 , c = 0.5 , d = 1.2
ESLPSO C R = 0.5 , F = 0.5 , c = 0.1 , M = N
Table 7. Wilcoxon rank sum test results of EECO and other competing algorithms.
Table 7. Wilcoxon rank sum test results of EECO and other competing algorithms.
EECO vs.
+/=/-
CEC-2017 Test Suite
10D30D50D100D
EDECO25/4/029/0/029/0/029/0/0
ISGTOA25/4/029/0/029/0/028/1/0
APSM-jSO23/4/226/0/327/0/224/3/2
LSHADE-SPACMA23/4/226/1/227/0/224/3/2
EOSMA23/4/229/0/029/0/029/0/0
GLSRIME23/5/128/1/029/0/027/2/0
EPSCA21/8/025/2/223/6/021/8/0
ESLPSO24/4/126/1/227/1/124/3/2
Table 8. Friedman test results of EECO and other competing algorithms.
Table 8. Friedman test results of EECO and other competing algorithms.
Test SuiteDimensionEECOEDECOISGTOAAPSM-jSOLSHADE-SPACMAEOSMAGLSRIMEEPSCAESLPSOp-Value
CEC-2017102.1386.4146.9664.2413.6216.2075.5174.9314.9663.71E-12
301.4836.8976.7243.7934.3107.4485.5173.3795.4482.38E-21
501.2077.2076.7243.6904.0697.4145.5523.5865.5525.62E-24
1001.3457.0006.4833.6903.6907.5526.5523.3795.3104.35E-25
Mean rank1.5436.8796.7243.8533.9227.1555.7843.8195.319N/A
Overall rank187349625N/A
Table 9. Experiments comparing EECO with other competing algorithms using corresponding population size.
Table 9. Experiments comparing EECO with other competing algorithms using corresponding population size.
No.IndexEECOECOEDECOISGTOAAPSM-jSOLSHADE-SPACMAEOSMAGLSRIMEEPSCAESLPSO
F1Best1.0002E+021.0666E+075.3039E+081.1882E+028.5243E+061.0086E+073.1477E+073.2824E+051.0000E+021.8355E+02
Avg3.4633E+021.5081E+081.5110E+092.7454E+031.4707E+071.3942E+074.5786E+077.0851E+051.0000E+027.2423E+03
Std9.5038E+021.7324E+087.3613E+083.2596E+034.2702E+062.0713E+061.4076E+074.0758E+051.0205E-097.3898E+03
Rank29103768514
F2Best3.0000E+023.1406E+041.2279E+042.0085E+045.2335E+034.0713E+033.0281E+045.7146E+033.0000E+023.4836E+02
Avg3.0000E+024.5059E+042.3419E+043.3115E+041.1271E+043.1166E+044.1500E+041.6717E+043.0000E+022.3970E+03
Std4.7476E-051.0953E+048.0982E+038.5638E+033.4608E+032.4188E+047.4724E+037.4384E+036.7928E-032.3566E+03
Rank11068479523
F3Best4.0000E+025.0544E+025.9254E+024.6679E+024.9713E+024.9279E+024.9771E+024.7852E+024.0026E+024.6876E+02
Avg4.0159E+025.5680E+026.9028E+025.0745E+025.1675E+024.9829E+025.3460E+025.2175E+024.6569E+024.9488E+02
Std2.0216E+002.9201E+017.6803E+012.4864E+011.1539E+013.9403E+001.5220E+013.6552E+014.7785E+011.6021E+01
Rank19105648723
F4Best5.2587E+026.2510E+026.4144E+025.6966E+026.7318E+026.6488E+025.9708E+025.3707E+025.5373E+025.3781E+02
Avg5.4391E+026.9282E+027.1821E+025.9683E+026.9967E+026.9119E+026.2902E+025.8326E+026.0351E+025.6481E+02
Std1.1072E+014.2995E+013.1051E+012.1147E+011.5795E+019.5705E+001.4125E+012.5505E+013.4847E+012.3486E+01
Rank18104976352
F5Best6.0083E+026.3012E+026.1833E+026.0153E+026.0339E+026.0431E+026.0251E+026.0335E+026.0025E+026.0001E+02
Avg6.0263E+026.4769E+026.3018E+026.0811E+026.0450E+026.0492E+026.0482E+026.0923E+026.1175E+026.0079E+02
Std1.4591E+001.0315E+017.1418E+004.7916E+007.0646E-013.5636E-011.4715E+003.3493E+001.4140E+011.1799E+00
Rank21096354781
F6Best7.5799E+029.0473E+029.3163E+028.0197E+029.2221E+028.8672E+028.5339E+028.0653E+027.9249E+027.7706E+02
Avg7.8412E+021.0923E+031.0130E+038.3930E+029.3361E+029.3261E+028.8058E+028.4485E+028.5611E+028.0191E+02
Std2.0643E+011.2298E+024.9454E+013.2468E+018.7529E+001.6240E+011.5305E+012.2496E+017.2626E+011.7981E+01
Rank11093876452
F7Best8.1691E+028.9381E+029.0226E+028.4975E+029.8314E+029.6879E+028.8151E+028.5115E+028.4490E+028.3781E+02
Avg8.3854E+029.4892E+029.8250E+028.8300E+029.9831E+029.9988E+029.1234E+028.8550E+028.9363E+028.6245E+02
Std1.5512E+012.6660E+013.4335E+011.7928E+019.9401E+001.2985E+011.9471E+011.7335E+013.1775E+012.0222E+01
Rank17839106452
F8Best9.1509E+023.4198E+031.8289E+031.0029E+039.2447E+029.2019E+029.3383E+021.0287E+039.5510E+029.0709E+02
Avg9.6117E+024.9803E+033.7534E+031.3566E+039.3527E+029.5019E+021.0403E+032.8395E+032.4155E+039.6526E+02
Std4.7488E+011.2327E+031.4570E+033.7236E+029.9517E+001.2270E+017.6847E+011.7226E+031.4781E+035.9133E+01
Rank31096125874
F9Best2.8773E+034.5867E+036.5101E+034.4384E+038.6932E+037.8571E+036.8543E+033.8793E+034.0528E+033.8480E+03
Avg4.7690E+035.7015E+037.4975E+037.0771E+038.8536E+038.5292E+037.3926E+034.5379E+035.1015E+034.9839E+03
Std7.7122E+025.5244E+026.6318E+021.2329E+031.2304E+023.7494E+022.5974E+025.5227E+027.6133E+026.6182E+02
Rank25861097143
F10Best1.1289E+031.2634E+031.2920E+031.1614E+031.2516E+031.2617E+031.2885E+031.2132E+031.1119E+031145.830
Avg1.1809E+031.4149E+031.4184E+031.2295E+031.2954E+031.2994E+031.3285E+031.2898E+031.1881E+031.2416E+03
Std5.2312E+011.3138E+028.9162E+014.8233E+012.3060E+012.4760E+012.4552E+015.0144E+014.8642E+0151.81430709
Rank19103678524
F11Best2.1217E+032.2676E+067.8723E+063.3165E+048.1508E+051.0060E+061.9866E+061.5908E+062.6860E+0320253.4945
Avg3.4859E+038.7382E+063.5060E+074.8977E+052.8398E+062.0884E+064.4211E+065.7738E+062.2353E+04184248.2761
Std1.5356E+034.3976E+062.4954E+074.2222E+051.0363E+064.8450E+051.9355E+064.2418E+062.7735E+04137801.6784
Rank19104657823
F12Best1.4342E+031.5840E+046.8309E+041.5642E+031.0454E+051.9293E+059.3801E+048.9797E+031.3293E+031922.892453
Avg1.9688E+031.5862E+051.7408E+051.4528E+043.7133E+054.9712E+052.8988E+053.9260E+041.3987E+0316527.31732
Std4.1827E+023.1803E+056.6446E+041.5802E+041.3717E+052.0112E+051.1831E+052.6510E+041.0609E+0219690.11727
Rank26739108514
F13Best1.4788E+032.7886E+031.6480E+031.6203E+031.7979E+032.1512E+031.5739E+037.6255E+031.5117E+031524.451052
Avg1.5135E+035.3163E+042.1678E+033.2955E+031.9475E+032.8751E+032.5317E+034.2317E+048.6166E+042105.770277
Std5.3282E+016.3146E+041.0257E+033.3811E+031.3626E+026.2659E+027.9175E+022.8415E+042.2787E+051268.647702
Rank19472658103
F14Best1.5815E+032.2874E+031.1776E+041.6442E+031.6452E+043.5940E+041.8829E+043.6940E+031.5094E+031762.681814
Avg1.7570E+031.4454E+042.9877E+048.3079E+033.5583E+046.3446E+044.2947E+041.5308E+041.5630E+037615.436605
Std8.2357E+011.1454E+041.2842E+048.3423E+031.2685E+042.1543E+041.6884E+041.2291E+044.6956E+0110029.45177
Rank25748109613
F15Best1.6169E+032.3499E+032.3269E+032.0244E+033.0114E+033.0242E+032.2652E+032.2036E+031.9875E+031902.168898
Avg2.0055E+032.8809E+033.1450E+032.4159E+033.4310E+033.2715E+032.6994E+032.6655E+032.6732E+032421.05883
Std2.3294E+023.4811E+022.9881E+022.3151E+022.0254E+021.5112E+022.4123E+022.3800E+024.1118E+02319.4655107
Rank17821096453
F16Best1.7666E+031.8397E+032.0277E+031.8101E+032.2746E+032.0383E+031.8866E+031.8106E+031.7515E+031776.714515
Avg1.8163E+032.2241E+032.2589E+032.0566E+032.4474E+032.3388E+032.0499E+032.1582E+032.2758E+031989.755998
Std3.4497E+012.8303E+021.5197E+021.4830E+027.4347E+011.3313E+029.9962E+012.4964E+022.9003E+02146.1895127
Rank16741093582
F17Best1.8504E+034.5316E+042.2311E+042.4691E+042.6405E+043.1821E+047.7773E+041.4108E+053.3309E+0323394.46988
Avg2.0062E+037.7655E+058.2441E+041.3067E+054.0943E+046.6430E+041.2170E+055.9382E+056.9747E+0485853.49497
Std9.5558E+011.3497E+064.2900E+041.9036E+051.1788E+042.1851E+043.4056E+043.6511E+056.7148E+0472715.98745
Rank11058237946
F18Best1.9656E+033.0807E+038.8543E+032.1070E+031.4125E+041.5740E+041.2324E+043.3755E+031.9115E+032056.546423
Avg2.0277E+031.4517E+041.1076E+059.5544E+032.8552E+044.7673E+044.8710E+041.6240E+041.9767E+038211.842954
Std4.5265E+011.2393E+041.1407E+057.3783E+031.0754E+042.1625E+042.6514E+041.3260E+041.0889E+028545.087761
Rank25104789613
F19Best2.0409E+032.3207E+032.3527E+032.1026E+032.6670E+032.6476E+032.2792E+032.2145E+032.0717E+032063.273556
Avg2.2514E+032.6051E+032.6169E+032.3633E+032.8630E+032.8472E+032.4410E+032.5035E+032.4774E+032342.110457
Std1.5766E+021.5900E+021.4438E+021.8792E+021.1100E+028.0219E+019.6795E+012.1337E+022.2810E+02198.9296812
Rank17831094652
F20Best2.3110E+032.2275E+032.4240E+032.3508E+032.4849E+032.4592E+032.3883E+032.3612E+032.3512E+032343.067091
Avg2.3397E+032.4474E+032.4809E+032.3722E+032.4995E+032.4919E+032.4102E+032.4096E+032.3841E+032358.622466
Std1.6298E+018.4701E+012.9743E+011.5172E+017.9571E+001.3082E+011.4954E+012.8969E+012.2133E+0111.6527675
Rank17831096542
F21Best2.3000E+032.3412E+032.6673E+032.3000E+032.3304E+032.3257E+032.3274E+032.3059E+032.3025E+032300
Avg2.5296E+033.7563E+036.1441E+032.6134E+032.3403E+032.3315E+032.3409E+035.2254E+036.2178E+033351.609735
Std8.8529E+022.3015E+033.0103E+031.2087E+035.5704E+004.8164E+007.6173E+001.5905E+031.7721E+031818.548534
Rank47952138106
F22Best2.6757E+032.7639E+032.7771E+032.7017E+032.8356E+032.8313E+032.7430E+032.6965E+032.7038E+032685.358794
Avg2.6987E+032.8736E+032.8699E+032.7518E+032.8587E+032.8516E+032.7712E+032.7699E+032.7382E+032714.712244
Std1.7032E+015.8767E+013.3452E+013.2589E+011.1832E+019.3416E+001.4915E+014.6313E+012.6602E+0124.31337661
Rank11094876532
F23Best2.8463E+032.9565E+032.9641E+032.8666E+032.9957E+032.9683E+032.8739E+032.8882E+032.8704E+032854.535314
Avg2.8840E+033.0611E+033.0319E+032.9007E+033.0187E+033.0110E+032.9244E+032.9229E+032.9246E+032890.809262
Std3.5917E+017.9901E+013.7227E+012.7112E+011.0942E+011.2909E+011.9006E+011.7063E+014.9960E+0135.53460198
Rank11093875462
F24Best2.8753E+032.9186E+032.9742E+032.8873E+032.8923E+032.8892E+032.8951E+032.8878E+032.8835E+032883.492632
Avg2.8798E+032.9744E+033.0436E+032.9038E+032.9010E+032.8920E+032.9127E+032.9107E+032.8881E+032890.814913
Std5.2929E+003.3228E+014.8366E+011.9004E+014.8665E+001.8164E+001.4488E+012.4058E+011.0481E+0111.16570171
Rank19106548723
F25Best2.8000E+033.7762E+033.8738E+032.8009E+035.3167E+035.1984E+033.6112E+032.9033E+034.3040E+033886.286574
Avg4.1081E+035.7975E+035.4866E+034.5041E+035.5753E+035.5068E+034.2135E+034.8421E+034.7132E+034326.449876
Std4.4718E+027.6867E+026.8761E+027.8022E+021.2903E+021.3799E+024.5937E+028.7589E+024.1669E+02339.4984132
Rank11074982653
F26Best3.1296E+033.2097E+033.2424E+033.2113E+033.2261E+033.2221E+033.2217E+033.2205E+033.1983E+033203.44455
Avg3.1818E+033.2676E+033.2904E+033.2342E+033.2381E+033.2301E+033.2410E+033.2449E+033.2287E+033225.80584
Std1.8643E+013.1587E+014.4358E+011.6999E+016.9512E+003.7903E+001.1642E+012.3599E+011.2545E+0115.60638933
Rank19105647832
F27Best3.1000E+033.2530E+033.3173E+033.2234E+033.2516E+033.2389E+033.2297E+033.2230E+033.1000E+033196.515686
Avg3.1658E+033.3715E+033.4898E+033.2521E+033.2704E+033.2527E+033.2666E+033.2556E+033.1618E+033227.114407
Std6.6245E+014.9180E+019.1542E+011.7315E+011.3263E+011.0587E+012.0342E+012.0105E+016.9239E+0125.1513953
Rank29104857613
F28Best3.3637E+033.6163E+034.1280E+033.4132E+034.0225E+033.8991E+033.7793E+033.7224E+033.5801E+033408.451426
Avg3.5718E+034.4258E+034.4271E+033.7060E+034.2215E+034.0720E+033.9616E+033.9641E+033.8797E+033712.883355
Std1.5403E+024.1655E+021.9062E+021.3982E+021.1022E+029.8138E+011.1614E+021.9860E+022.4113E+02198.7913483
Rank19102875643
F29Best3.4220E+033.6234E+041.6772E+055.7725E+031.1301E+051.0762E+059.2716E+043.7939E+045.3648E+035296.087599
Avg7.0266E+033.2390E+051.4152E+061.0034E+042.1310E+051.9048E+054.3292E+052.4792E+057.4678E+038673.580642
Std3.8217E+032.6737E+051.2694E+063.2542E+035.8247E+045.1902E+042.1164E+052.3098E+051.8547E+032537.319778
Rank18104659723
Friedman Rank1.4148.2418.5174.3456.7936.5526.3105.7934.0692.966
+/=/−N/A29/0/029/0/027/2/027/1/127/1/127/1/128/1/021/4/421/7/1
Table 10. Details of real-world constrained engineering optimization problems.
Table 10. Details of real-world constrained engineering optimization problems.
ProblemNameD
RW01Tension/compression spring design problem3
RW02Pressure vessel design problem4
RW03Three-bar truss design problem2
RW04Welded beam design problem4
RW05Speed reducer design problem7
RW06Gear train design problem4
RW07Cantilever beam design problem5
RW08Multiple disk clutch brake design problem5
RW09Step-cone pulley problem5
Table 11. Experiments comparing EECO with other competing algorithms at constrained engineering optimization problems.
Table 11. Experiments comparing EECO with other competing algorithms at constrained engineering optimization problems.
No.IndexEECOEDECOISGTOAAPSM-jSOLSHADE-SPACMAEOSMAGLSRIMEEPSCAESLPSO
RW1Best1.2666E-021.2756E-021.2787E-021.7773E-021.2666E-021.2672E-021.3113E-021.2666E-021.2720E-02
Mean1.2771E-021.3704E-021.3109E-021.7775E-021.2684E-021.2869E-021.6981E-021.3944E-021.2882E-02
Std2.0705E-049.8361E-043.8124E-042.9736E-062.7940E-052.2313E-042.3095E-031.8742E-032.3411E-04
Rank265913874
RW2Best5.8504E+036.3582E+036.0758E+036.2707E+036.4653E+036.2087E+036.2595E+035.8728E+035.8770E+03
Mean6.0591E+038.6606E+036.6352E+036.4423E+037.5240E+036.8430E+037.1244E+036.4951E+036.3556E+03
Std2.3813E+021.2218E+034.8391E+022.7207E+021.8974E+033.6300E+028.8165E+026.2261E+023.7441E+02
Rank195386742
RW3Best2.6389E+022.6389E+022.6389E+022.6389E+022.6389E+022.6389E+022.6389E+022.6389E+022.6389E+02
Mean2.6389E+022.6389E+022.6391E+022.6389E+022.6389E+022.6390E+022.6466E+022.6393E+022.6389E+02
Std5.9918E-146.7365E-031.3135E-027.8658E-106.8317E-141.4456E-029.0553E-014.5358E-024.9570E-03
Rank147316985
RW4Best1.6928E+001.7288E+001.7370E+001.0890E+151.6928E+001.7030E+001.7213E+001.6999E+001.7152E+00
Mean1.6928E+002.0392E+001.7792E+001.0890E+151.6928E+001.7489E+001.9902E+001.7726E+001.7668E+00
Std6.7949E-052.2470E-013.8263E-028.2773E+046.4020E-063.7259E-021.7265E-011.2312E-017.8868E-02
Rank286913754
RW5Best2.8732E+032.9960E+032.9937E+031.2708E+072.9936E+033.0033E+032.9976E+032.9936E+032.9947E+03
Mean2.8734E+033.0031E+032.9940E+031.2708E+072.9936E+033.0133E+033.0105E+032.9936E+032.9962E+03
Std1.0284E-014.0047E+003.0598E-011.4755E-011.9172E-035.3050E+001.5672E+015.5850E-041.1368E+00
Rank164938725
RW6Best2.7009E-122.7009E-122.7009E-122.7009E-122.7009E-122.3078E-112.3078E-112.3078E-112.7009E-12
Mean5.0620E-105.2116E-095.8190E-107.9145E-102.7299E-101.1105E-094.2618E-098.0077E-091.1875E-09
Std1.0261E-091.2218E-087.2954E-109.0042E-103.8346E-106.3158E-106.0422E-091.3910E-087.9503E-10
Rank283415796
RW7Best1.3400E+001.3524E+001.3431E+001.3400E+001.3400E+001.3459E+001.3526E+001.3401E+001.3520E+00
Mean1.3400E+001.5506E+001.3635E+001.3400E+001.3405E+001.3536E+001.4338E+001.3430E+001.3756E+00
Std6.7764E-082.2988E-011.5331E-023.3567E-054.5479E-046.5782E-038.8386E-023.7741E-032.5766E-02
Rank196235847
RW8Best3.9247E+083.9247E+083.9247E+081.3400E+091.3510E+093.9247E+083.9247E+083.9247E+083.9247E+08
Mean3.9247E+083.9247E+083.9247E+081.3647E+091.3747E+093.9247E+083.9247E+083.9247E+083.9247E+08
Std6.2829E-086.2829E-086.2829E-087.8338E+077.4639E+076.2829E-086.2829E-086.2829E-086.2829E-08
Rank111891111
RW9Best1.6085E+011.6304E+011.6754E+011.0098E+111.6089E+011.6849E+011.6306E+011.6111E+011.6141E+01
Mean1.6086E+011.6687E+011.7097E+011.0098E+111.6101E+011.7377E+011.7506E+011.6516E+011.6769E+01
Std1.0423E-043.3065E-012.6577E-011.1988E+026.6970E-033.3127E-011.4142E+001.7645E-014.6407E-01
Rank146927835
Friedman Rank1.7226.4445.1116.2223.2785.2227.2225.1114.667
+/=/−N/A7/2/07/2/08/1/05/3/17/2/08/1/06/3/06/3/0
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MDPI and ACS Style

Li, N.; Miao, Z.; Zhou, S.; Zhou, H.; Wang, M.; Liu, Z. An Enhanced Educational Competition Optimizer Integrating Multiple Mechanisms for Global Optimization Problems. Biomimetics 2025, 10, 719. https://doi.org/10.3390/biomimetics10110719

AMA Style

Li N, Miao Z, Zhou S, Zhou H, Wang M, Liu Z. An Enhanced Educational Competition Optimizer Integrating Multiple Mechanisms for Global Optimization Problems. Biomimetics. 2025; 10(11):719. https://doi.org/10.3390/biomimetics10110719

Chicago/Turabian Style

Li, Na, Zi Miao, Sha Zhou, Haoxiang Zhou, Meng Wang, and Zhenzhong Liu. 2025. "An Enhanced Educational Competition Optimizer Integrating Multiple Mechanisms for Global Optimization Problems" Biomimetics 10, no. 11: 719. https://doi.org/10.3390/biomimetics10110719

APA Style

Li, N., Miao, Z., Zhou, S., Zhou, H., Wang, M., & Liu, Z. (2025). An Enhanced Educational Competition Optimizer Integrating Multiple Mechanisms for Global Optimization Problems. Biomimetics, 10(11), 719. https://doi.org/10.3390/biomimetics10110719

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