Light Field Optimization for Optical Wireless Power Transfer by Peiyuan Xu, Wenjia Zhang, Zuyuan He

“…In this paper, we propose and compare the Gerchberg-Saxton algorithm, direct binary search and genetic algorithm enabled light field optimization for adapting photovoltaic cells in different geometric arrangements. …”
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Deep Reinforcement Learning-Based Attention Decision Network for Agile Earth Observation Satellite Scheduling by Dongning Liu, Guanghui Zhou

“…A comprehensive experiment was conducted, and the results proved that the attention mechanism in our ADN was beneficial for the training process to converge to better strategies. Compared with other advanced algorithms, the proposed method obtained a better total profit in the test sets. …”
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A Comparative Study of EAG and PBIL on Large-Scale Global Optimization Problems by Imtiaz Hussain Khan

“…Evolutionary Algorithm with Guided Mutation (EAG) combines global statistical information and location information to sample offspring, aiming that this hybridization improves the search and optimization process. …”
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Comparative study of defects in graphene flake grown on amorphous and crystalline copper surfaces by Laura Arango-Tabares, Julian D Correa, Olga Lopez-Acevedo

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A Multi-Strategy Adaptive Coati Optimization Algorithm for Constrained Optimization Engineering Design Problems by Xingtao Wu, Yunfei Ding, Lin Wang, Hongwei Zhang

“…The coati optimization algorithm (COA) is a novel meta-heuristic algorithm known for its robust search capabilities and rapid convergence rate. …”
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A Comparative Analysis of Swarm Intelligence Techniques for Feature Selection in Cancer Classification by Chellamuthu Gunavathi, Kandasamy Premalatha

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An Improved Human Evolution Optimization Algorithm for Unmanned Aerial Vehicle 3D Trajectory Planning by Xue Wang, Shiyuan Zhou, Zijia Wang, Xiaoyun Xia, Yaolong Duan

“…Furthermore, in the loser update strategy, an adaptive <i>t</i>-distribution perturbation strategy is utilized for its small mutation amplitude, which enhances the local search capability and robustness of the algorithm. …”
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Low-carbon economic optimization for flexible DC distribution networks based on the hiking optimization algorithm by Ke Wu, Yuefa Guo, Ke Wang, Zhenliang Chen

“…The results indicate that the total cost and carbon emissions of the system decreased by 8.98% and 15.13%, respectively, indicating that appropriate scheduling of the carbon trading mechanism and flexible loads effectively improves the system’s economic and environmental performance. In addition, a comparative study with traditional particle swarm and genetic algorithms demonstrates that the HOA, by incorporating adaptive mechanisms for both search space resolution and speed adjustment, enhances both global exploration and local exploitation, effectively avoiding local optima traps. …”
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Social Cognitive Optimization Algorithm for Approximate Path Generation Synthesis of Spherical 4R Linkage by Che Linxian, Huang Yonggang, Du Li

“…Combining the self-adaptive penalty function method，this study employs the social cognitive optimization (SCO) algorithm to solve the aforementioned problem. In order to enhance the convergence speed and accuracy of SCO algorithm，a novel accelerating social cognitive optimization (ASCO) algorithm is proposed in which the differential evolution (DE) operators are used to local search. …”
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A modified perturb and observe MPPT algorithm for PEMFC with rapid convergence and low power oscillation by Resat Celikel, Omur Aydogmus, Musa Yilmaz

“…Its performance is evaluated in a MATLAB/Simulink environment under five different scenarios. A comparative analysis is conducted against the conventional P&O and optimization-based MPPT algorithms, including Particle Swarm Optimization (PSO), Cuckoo Search Algorithm (CSA), and Genetic Algorithm (GA). …”
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Hybrid Clustering-Enhanced Brain Storm Optimization Algorithm for Efficient Multi-Robot Path Planning by Guangping Qiu, Jizhong Deng, Jincan Li, Weixing Wang

“…This strategy effectively balances global exploration with local exploitation, thereby enhancing solution diversity and search depth. Comparative analyses against the standard Brain Storm Optimization (BSO) and other prominent swarm intelligence algorithms reveal that HC-BSO exhibits significant advantages in terms of total path length, computational time, and path conflict avoidance. …”
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A Novel Rolling Bearing Fault Diagnosis Method Based on the NEITD-ADTL-JS Algorithm by Shi Zhuo, Xiaofeng Bai, Junlong Han, Jianpeng Ma, Bojun Sun, Chengwei Li, Liwei Zhan

“…In addition, fault diagnosis parameters are adaptively optimized using an improved adaptive deep transfer learning (ADTL) network combined with the Jellyfish Search (JS) algorithm, further enhancing diagnostic performance. …”
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Comparative proteomic study of pig muscle proteins during growth and development of an animal by A. G. Akhremko, E. S. Vetrova

“…The mass spectrometric identification was conducted with the help of the high-performance liquid chromatography (HPLC) system connected to a mass spectrometer; further the data were interpreted by search algorithm Andromeda. When comparing frequency diagrams of one-dimensional electrophoregrams of all three muscle tissues of weaned pigs, the greatest difference was observed for the muscle sample l. dorsi. …”
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Multi strategy Horned Lizard Optimization Algorithm for complex optimization and advanced feature selection problems by Marwa M. Emam, Mosa E. Hosney, Reham R. Mostafa, Essam H. Houssein

“…The efficacy of mHLOA is rigorously evaluated using 12 complex benchmark functions from the CEC’22 test suite and 14 standard datasets from the UCI Machine Learning Repository. Comparative analysis against recent state-of-the-art algorithms demonstrates that mHLOA achieves superior classification accuracy, selects a reduced yet highly effective feature subset, and exhibits robustness in high-dimensional FS tasks. …”
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Multi-objective particle swarm optimization algorithm for task allocation and archived guided mutation strategies by Jianjie Chen, Yanmin Liu, Yi Luo, Aijia Ouyang, Jie Yang, Wuer Bai

“…Abstract In this paper, we propose a novel multi-objective particle swarm optimization algorithm with a task allocation and archive-guided mutation strategy (TAMOPSO), which effectively solves the problem of inefficient search in traditional algorithms by assigning different evolutionary tasks to particles with different characteristics. …”
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3D Flight Path Planning for UAV Based on Improved Particle Swarm Optimization Algorithm by Cunjie Li, Qingli Zhao, Canyi Che

“…The algorithm enhances early stage global search capability and later period local optimization capability compared to traditional particle swarm algorithm. …”
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Solving the Problem of Vehicle Routing Problem With Time Window via Dual Adaptive Genetic Algorithm by Chunge Hua

“…To address the Vehicle Routing Problem with Time Windows (VRPTW), this paper presents a novel Dual Adaptive Genetic Algorithm (DAGA). While numerous metaheuristic algorithms have been proposed to solve VRPTW, most existing approaches either rely on fixed cost functions or incorporate local search heuristics without adaptive control. …”
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Intelligent decision-making for mine airflow on demand based on the improved artificial bee colony algorithm by ZHANG Lang, LEI Shuang, LI Wei, LIU Yanqing

“…The Lagrange relaxation method was used to optimize the model's constraint conditions, the conflict count method was used to optimize the objective function of the model, and random search methods combined with heuristic algorithms were used to optimize the search strategy of the model. …”
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Binary phase-coded radar waveform optimization based on improved hybrid quantum genetic algorithm by Yu ZHANG, Jing ZHAO, Yanguo JIA, Xiumin SHEN

“…To overcome the problem of single search focus and limited application scope of existing algorithm, a binary phase-coded radar waveform optimization (RWO) based on improved hybrid quantum genetic algorithm (IHQGA) was proposed.IHQGA adopted a novel self-adaptive rotation angle strategy, which dynamically adjusted the rotation angle based on evolutionary process and cosine similarity.The convergence speed, global search capability, and solution quality were improved.Simulation results demonstrate that compared with genetic algorithms, basic quantum genetic algorithms, and hybrid quantum genetic algorithms, IHQGA performs better in terms of solution quality and resource consumption for six benchmark functions that include single-peak, multi-peak, and non-convex optimization problems.Additionally, for binary phase-coded RWO, which verifies the feasibility and effectiveness of IHQGA in WO.…”
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FixedSum: A Novel Algorithm for Generating Weight Vectors in Decomposition-Based Multiobjective Optimization by Syed Zaffar Qasim, Muhammad Ali Ismail

“…These weight vectors are more uniformly spread in the search space, and we have compared our results with other methods on 5D, 8D, 10D and 12D weight vectors. …”
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