In mechanism design with symmetrical or asymmetrical motions, obtaining high precision of the input path given by working requirements of mechanisms can be a challenge for dimensional optimization. This study proposed a novel hybrid-combined differen...
An efficient satellite image segmentation method based on a hybrid grasshopper optimization algorithm (GOA) and minimum cross entropy (MCE) is proposed in this paper. The proposal is known as GOA–jDE, and it merges GOA with self-adaptive differ...
This study presents the Hybrid COASaDE Optimizer, a novel combination of the Crayfish Optimization Algorithm (COA) and Self-adaptive Differential Evolution (SaDE), designed to address complex optimization challenges and solve engineering design probl...
The localization of a passive target based on time-difference-of-arrival (TDOA) measurements is a complex task in mixed line-of-sight/non-line-of-sight (LOS/NLOS) environments, where the NLOS propagation introduces additional positive range biases. T...
Environmental and economic considerations create a challenge for manufacturers. The main priorities for production planning in environmentally friendly manufacturing industries are reducing energy consumption and improving productivity by balancing m...
In this paper, a hybrid differential evolution and weight total least squares method (HDE-WTLSM) is proposed for antenna array pattern synthesis. A variable diagonal weight matrix is introduced in total least squares method. Then, the weight matrix i...
A hybrid differential evolution (HDE) algorithm that minimizes the total earliness and tardiness time (ET), a just-in-time objective, is studied for a single-batch-processing machine (SBPM) scheduling problem with different processing times, release...
In this paper, we address the problem of detecting and tracking targets with a low signal-to-noise ratio (SNR) by exploiting hybrid differential evolution (HDE) in the particle filter track-before-detect (PF-TBD) context. Firstly, we introduce the Ba...
Aiming to address the problem of selecting the parameters of a soil constitutive model in the calculation of foundation pit stability, this paper proposes a hybrid genetic differential evolution algorithm (GADE) which performs by “jumping out o...
This paper considers the problem of constrained multi-objective non-linear optimization of planetary gearbox based on hybrid metaheuristic algorithm. Optimal design of planetary gear trains requires simultaneous minimization of multiple conflicting o...
Label placement is a difficult problem in automated map production. Many methods have been proposed to automatically place labels for various types of maps. While the methods are designed to automatically and effectively generate labels for the point...
With the development of smart agriculture, autopilot technology is being used more and more widely in agriculture. Because most of the current global path planning only considers the shortest path, it is difficult to meet the articulated steering tra...
Traditional particle swarm optimization (PSO) easily falls into premature convergence, while differential evolution (DE) is highly sensitive to fixed control parameters. Existing PSO-DE hybrid frameworks suffer from static population sizes and insuff...
In Global Navigation Satellite Systems (GNSS), high-precision position coordinates are typically determined by establishing a double-difference carrier phase observation model and resolving the integer ambiguities within it. Therefore, the ability to...
Techno-economic optimization of a standalone solar/wind/battery hybrid system located in Xining, China, is the focus of this paper, and reliable and economic indicators are simultaneously employed to address the problem. To obtain a more precise Pare...
This paper presents the Hybrid and Self-Adaptive Differential Evolution algorithms (HSADE) to solve an egg distribution problem in Thailand. We introduce and formalize a model for a multi-product, multi-depot vehicle routing problem with a time windo...
The optimization and allocation of transport cost savings among stakeholders are two important issues that influence the satisfaction of information providers, drivers and passengers in ridesharing recommendation systems. For optimization issues, fin...
The research proposes a new oppositional sine cosine muted differential evolution algorithm (O-SCMDEA) for the optimal allocation of distributed generators (OADG) in active power distribution networks. The suggested approach employs a hybridization o...
Due to the increasing level of customization and globalization of competition, rescheduling for distributed manufacturing is receiving more attention. In the meantime, environmentally friendly production is becoming a force to be reckoned with in int...
This study addresses pressure regulation in an induction-motor-driven centrifugal fan and introduces two complementary novelties: a Softsign-PI controller that shapes the tracking error via a Softsign nonlinearity before PI regulation and a hybrid st...
The iterative Fourier transform algorithm (IFTA) is widely used in various optical communication applications based on liquid crystal on silicon spatial light modulators. However, the traditional iterative method has many disadvantages, such as a poo...
We developed a hybrid algorithm for multi-objective design of water distribution networks (WDNs) in the present study. The proposed algorithm combines the global search schemes of differential evolution (DE) with the local search capabilities of harm...
This study focuses on the challenge of short-term economic dispatch in hybrid generation systems, specifically under scenarios where energy constraints arise due to reduced water availability. The primary aim is to compare various generation scenario...
Global optimization is critical in engineering, computer science, and various industrial applications as it aims to find optimal solutions for complex problems. The development of efficient algorithms has emerged from the need for optimization, with...
Sustainable development of transport systems is a common topic of concern and effort in multiple countries, in which reducing carbon emissions is one of the core goals. Multimodal transport is an effective way to achieve carbon emission reduction and...
Bag-of-Tasks (BoT) scheduling over cloud computing resources called Cloud Bag-of-Tasks Scheduling (CBS) problem, which is a well-known NP-hard optimization problem. Whale Optimization Algorithm (WOA) is an effective method for CBS problems, which sti...
Community detection (CD) has become an important research direction for data mining in complex networks. Evolutionary algorithm-based (EA-based) approaches, among many other existing community detection methods, are widely used. However, EA-based app...
The calibration of cameras plays a critical role in close-range photogrammetry because the precision of calibration has a direct effect on the quality of results. When handling image capture using a camera, traditional swarm intelligence algorithms s...
In this paper, a new hybrid whale optimization algorithm (WOA) called WOA-DE is proposed to better balance the exploitation and exploration phases of optimization. Differential evolution (DE) is adopted as a local search strategy with the purpose of...
As one of the most promising forms of renewable energy, solar energy is increasingly deployed. The simulation and control of photovoltaic (PV) systems requires identification of their parameters. A Hybrid Adaptive algorithm based on JAYA and Differen...
The MASW (Multichannel Analysis of Surface Waves) method oriented toward seismic microzoning has been evolving consistently and steadily for several decades, providing increasingly reliable solutions that are consistent with field and laboratory data...
To solve the limitations of single optimization algorithms, such as premature convergence, insufficient global exploration, and high susceptibility to local optima, a Hybrid Optimization Algorithm (HOA) based on multi-subpopulation collaboration and...
Accurate segmentation of brain tumors in magnetic resonance imaging (MRI) remains a challenging task due to heterogeneous tumor structures, varying intensities across modalities, and limited annotated data. Deep learning has significantly advanced se...
In this study, we present and discuss a variant of the classic vehicle routing problem (VRP), the green automated guided vehicle (AGV) routing problem, which involves simultaneous pickup and delivery with time windows (GVRPSPDTW) in an intelligent wo...
Hyperspectral image (HSI) analysis has become one of the most active topics in the field of remote sensing, which could provide powerful assistance for sensing a larger-scale environment. Nevertheless, a large number of high-correlation and redundanc...
Today, the economic production of energy and its transmission at the lowest possible cost is one of the most important issues in various fields of engineering. Therefore, one of the most important optimization problems in power systems and electrical...
With the emergence of the smart grid (SG), real-time interaction is favorable for both residents and power companies in optimal load scheduling to alleviate electricity cost and peaks in demand. In this paper, a modular framework is introduced for ef...
In the real world, forming a team of two or more people to solve a problem collaboratively is common to take advantage of the complementarity of the values and skills of team members. This idea can be used to develop more effective hybrid solution al...
This paper introduces TRIDENT-DE, a novel ensemble-based variant of Differential Evolution (DE) designed to tackle complex continuous global optimization problems. The algorithm leverages three complementary trial vector generation strategies best/1/...
The proposed Adaptive RTR with Quarantine (ARQ) method integrates, within a single evolutionary scheme for continuous optimization, three mature ideas of pbest differential evolution with an archive, success-history parameter adaptation, and restrict...
Multi-objective task graph scheduling is a well-known NP-hard problem that plays a significant role in heterogeneous distributed systems. The solution to the problem is expected to optimize all scheduling objectives. Pretty large state-of-the-art alg...
Differential evolution is a popular algorithm for solving global optimization problems. When tested, it has reportedly outperformed both robotic problems and benchmarks. However, it may have issues with local optima or premature convergence. In this...
Due to the complex structure of the angle grinder and the existence of multiple rotating parts, the coupling phenomenon of the data results in the complexity and chaos of the data. The market scale of angle grinder is huge. Manual diagnosis and tradi...
Model-based and data-driven methods are commonly used in leak location strategies in water distribution networks. This paper formulates a hybrid methodology in two stages that complements the advantages and disadvantages of data-driven and model-base...
The selection of critical features from microarray data as biomarkers holds significant importance in disease diagnosis and drug development. It is essential to reduce the number of biomarkers while maintaining their performance to effectively minimi...
Since the discovery of the Differential Evolution algorithm, new and improved versions have continuously emerged. In this paper, we review selected algorithms based on Differential Evolution that have been proposed in recent years. We examine the mec...
A multi-objective evolutionary algorithm based on decomposition (MOEA/D) serves as a robust framework for addressing multi-objective optimization problems (MOPs). However, it is widely recognized that the applicability of a fixed offspring-generating...
A hybrid optimization method for the synthesis of a sparse conformal array with the verification of a truncated cone antenna array is proposed in this manuscript. This array synthesis is studied aiming at enhancing axial radiation and reducing the pe...
A significant amount of the literature is focused on converters that supply the required voltage with low input-current ripple to electronic devices. A hybrid converter that combines boost and Cuk converters was developed recently. This hybrid conver...
This study provides an effective cooperative carrying and navigation control method for mobile robots in an unknown environment. The manager mode switches between two behavioral control modes—wall-following mode (WFM) and toward-goal mode (TGM)...
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