We present efficient sequential and parallel algorithms for the maximum sum (MS) problem, which is to maximize the sum of some shape in the data array. We deal with two MS problems; the maximum subarray (MSA) problem and the maximum convex sum (MCS)...
As one of the common methods to construct classifiers, naïve Bayes has become one of the most popular classification methods because of its solid theoretical basis, strong prior knowledge learning characteristics, unique knowledge expression forms, a...
In many non-deterministic search algorithms, particularly those analogous to complex biological systems, there are a number of inherent difficulties, and the Bees Algorithm (BA) is no exception. The BA is a population-based metaheuristic search algor...
Clinical algorithms for child tuberculosis (TB) are a valuable guide for healthcare workers to initiate treatment. We evaluated the agreement of pediatric TB diagnosis using the current Indonesia diagnostic algorithms with the 2022 WHO treatment deci...
Huffman encoding and arithmetic coding algorithms have shown great potential in the field of image compression. These algorithms are the origin of current image compression techniques. Nevertheless, there are some deficiencies in both algorithms that...
Foundational algorithm instruction at the elementary level has centered on understanding control structures and reproducing given procedures; opportunities for learners to generate strategies and judge efficiency under varying data conditions remain...
In this paper, a new hybrid algorithm based on two meta-heuristic algorithms is presented to improve the optimization capability of original algorithms. This hybrid algorithm is realized by the deep ensemble of two new proposed meta-heuristic methods...
This paper presents a novel metaheuristic optimization algorithm inspired by the geometrical features of circles, called the circle search algorithm (CSA). The circle is the most well-known geometric object, with various features including diameter,...
Grey wolf optimizer (GWO) is a meta-heuristic algorithm inspired by the hierarchy of grey wolves (Canis lupus). Fireworks algorithm (FWA) is a nature-inspired optimization method mimicking the explosion process of fireworks for optimization problems....
A new algorithm, Material Generation Algorithm (MGA), was developed and applied for the optimum design of engineering problems. Some advanced and basic aspects of material chemistry, specifically the configuration of chemical compounds and chemical r...
The Nash social welfare (NSW) problem is relevant not only to the economic domain but also extends its applicability to the field of computer science. However, maximizing Nash social welfare is an APX-hard problem. In this study, we propose two appro...
The PID control algorithm for balancing robot attitude control suffers from the problem of difficult parameter tuning. Previous studies have proposed using metaheuristic algorithms to tune the PID parameters. However, traditional metaheuristic algori...
In this paper, a Firefly algorithm is proposed for identification and comparative study of five, seven and eight parameters of a single and double diode solar cell and photovoltaic module under different solar irradiation and temperature. Further, a...
Gate-level circuit partitioning is an important development trend for improving the efficiency of simulation in EDA software. In this paper, a gate-level circuit partitioning algorithm, based on clustering and an improved genetic algorithm, is propos...
The existing target tracking algorithm of the tennis dynamic image serving path cannot correct the serving path in time according to the physical characteristics of the target, resulting in poor correction accuracy and stability. To this end, this pa...
From collective intelligence to evolutionary computation and machine learning, symmetry can be leveraged to enhance algorithm performance, streamline computational procedures, and elevate solution quality. Grasping and leveraging symmetry can give ri...
RPL (routing protocol for low-power and lossy networks) is an important candidate routing algorithm for low-power and lossy network (LLN) scenarios. To solve the problems of using a single routing metric or no clearly weighting distribution theory of...
In this paper, we propose a novel methodology that combines the opposition Nelder–Mead algorithm and the selection phase of the genetic algorithm. This integration aims to enhance the performance of the overall algorithm. To evaluate the effect...
In the field of manufacturing, complex products with a tree structure often naturally exhibit asymmetric characteristics due to the uniqueness of their constituent elements and hierarchical relationships. In the production scheduling of such small-ba...
In terms of mobile robot path planning, the traditional A* algorithm has the following problems: a long searching time, an excessive number of redundant nodes, and too many path-turning points. As a result, the shortest path obtained from planning ma...
The fireworks algorithm (FWA) has achieved significant global optimization ability by organizing multiple simultaneous local searches. By dynamically decomposing the target problem and handling each one with a sub-population, it has presented distinc...
In the research and practice of integrated scheduling problems, the tree structure of complex products usually presents an asymmetric and complex form. This asymmetry is mainly reflected in the hierarchical relationship between the various components...
The Vehicle Routing Problem with Time Window (VRPTW) is of crucial importance in modern societies, where the aim is to optimize resource utilization, reduce costs and address constraints such as time and vehicle capacity. Traditional genetic algorith...
To improve the current indoor positioning algorithms, which have insufficient positioning accuracy, an ultra-wideband (UWB) positioning algorithm based on the Levenberg–Marquardt algorithm with improved Kalman filtering is proposed. An alternat...
This paper introduces a novel population-based bio-inspired meta-heuristic optimization algorithm, called Blood Coagulation Algorithm (BCA). BCA derives inspiration from the process of blood coagulation in the human body. The underlying concepts and...
Of all the renewable power generation technologies, solar tower power system is expected to be the most promising technology that is capable of large-scale electricity production. However, the optimization of heliostat field layout is a complicated p...
Inspired by the process of migration and reproduction of flora, this paper proposes a novel artificial flora (AF) algorithm. This algorithm can be used to solve some complex, non-linear, discrete optimization problems. Although a plant cannot move, i...
The disruptions in this era have caused a leap forward in information technology being applied in organizations to create a competitive advantage. In particular, we see this in tourism services, as they provide the best solution and prompt responses...
Numerous optimization problems have been defined in different disciplines of science that must be optimized using effective techniques. Optimization algorithms are an effective and widely used method of solving optimization problems that are able to...
In the process of the integrated scheduling of multi-variety and small-batch complex products, the process structure and attribute characteristics are often ignored, which affects the overall scheduling effect. Aiming at solving this problem, a heuri...
The efficiency and smoothness of path planning algorithms are critical factors influencing their practical applications. A traditional A* algorithm suffers from limitations in search efficiency, path smoothness, and obstacle avoidance. To address the...
Based on bee foraging behaviour, the Bees Algorithm (BA) is an optimisation metaheuristic algorithm which has found many applications in both the continuous and combinatorial domains. The original version of the Bees Algorithm has six user-selected p...
Although algorithms make more accurate forecasts than humans in many applications, decision-makers often refuse to resort to their use. In an economic experiment, we examine whether the extent of this phenomenon known as algorithm aversion can be red...
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Camera calibration is a core task in computer vision. Traditional calibration methods usually achieve approximate solutions due to the complexity of solving nonlinear equations, resulting in reprojection errors. This article proposes a camera calibra...
Validating the contributions of new algorithms is a critical step in hyperspectral anomaly detection (HAD) research. Typically, validation involves comparing the performance of a proposed algorithm against other algorithms using a series of benchmark...
With the rapid development of the economy and the continuous improvement of people’s living standards, the printing and packaging industry plays an increasingly important role in people’s lives. The traditional printing industry is a disc...
6 February 2023
While many online labor platforms have adopted algorithms to monitor or control workforces as a new form of algorithm management, there is no academic attempt to empirically examine how the algorithmic control of platforms influences platform workers...
Metaheuristic algorithms are widely used to find optimal or near-optimal solutions for complex problems by taking inspiration from natural behaviors and processes. Although many different methods have been developed, a common problem in many of them...
At present, the development of animation-based works for human–computer interaction applications has increased. To generate animations, actions are pre-recorded and animation flows are configured. In this research, from two images of letters of...
This study presents a swarm-control algorithm to overcome the limitations inherent to single-object systems. The leader–follower swarm-control method was selected for its ease of mathematical interpretation and theoretical potential for the unl...
Feature selection (FS) is a vital step in data mining and machine learning, especially for analyzing the data in high-dimensional feature space. Gene expression data usually consist of a few samples characterized by high-dimensional feature space. As...
Optimization techniques keep road performance at a good level using a cost-effective maintenance strategy. Thus, the trade-off between cost and road performance is a multi-objective function. This paper offers a new multi-objective stochastic algorit...
The chi-squared automatic interaction detector (CHAID) algorithm is considered to be one of the most used supervised learning methods as it is adaptable to solving any kind of problem at hand. We are keenly aware of the non-linear relationships among...
Computing interactions among cells is computationally complex in multicellular molecular communication simulations, making the design of efficient algorithms crucial. We review simulation algorithms for computing interactions among cells in multicell...
This paper introduces an evolutionary algorithm for n-dimensional single objective optimization problems: One-Dimensional Subspaces Optimization Algorithm (1D-SOA). The algorithm starts with an initial population in randomly selected positions. For e...
Nature-inspired metaheuristic algorithms remain a strong trend in optimization. Human-inspired optimization algorithms should be more intuitive and relatable. This paper proposes a novel optimization algorithm inspired by a human search party. We hyp...
The localization of sensor nodes is an important problem in wireless sensor networks. The DV-Hop algorithm is a typical range-free algorithm, but the localization accuracy is not high. To further improve the localization accuracy, this paper designs...
Aiming at the problems of significant communication overheads, the low reliability of primary nodes, and the insufficient dynamic adaptability of traditional consensus algorithms in intellectual property transaction scenarios, an Improved Practical B...
A reservoir dam is a water conservancy project with large investment and high social and economic benefits, which plays an irreplaceable role in flood control, power generation, water storage, and urban water supply. There is a risk of accidents in t...
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