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  1. 1101
  2. 1102

    Exploring the Orca Predation Algorithm for Economic Dispatch Optimization in Power Systems by Vivi Aida Fitria, Arif Nur Afandi, Aripriharta

    Published 2024-09-01
    “…This research shows that Orca Predation Algorithm consistently does better than other bio-inspired algorithms like Particle Swarm Optimization, Whale Optimization Algorithm, Grey Wolf Optimizer, the Bat Algorithm, Genetic Algorithm and Ant Colony Optimization in terms of minimum cost, average cost, and solution stability. …”
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    Article
  3. 1103
  4. 1104

    Optimal Trajectory Optimization of 7R Robot for Space Maintenance Operation by Qidong Li, Hehua Ju, Pengfei Xiao, Feifei Chen, Fei Lin

    Published 2025-01-01
    “…Finally, a hybrid optimization algorithm is proposed to solve the trajectory optimization problem of space robots by combining genetic algorithm and particle swarm optimization method. …”
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    Article
  5. 1105

    Improved Firefly Algorithm Based on Heuristic Information by CUI Jia-rui, LI Qing, YANG Liu-yi, WANG Heng, ZHANG Bo-yu

    Published 2019-02-01
    “…Firefly Algorithm (FA) is an optimization algorithm based on swarm intelligence which mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies With the aim to address the disadvantages of the firefly algorithm of slow convergence speed and ease of falling into the local optimum in the later period of the evolution process, the firefly algorithm is improved herein Two kinds of heuristic information are proposed into the algorithm to guide the convergence of the algorithm The first one takes the current global best as the heuristic information referencing the “global optimal” idea in particle swarm optimization, therefore, an algorithm called FAGO (Firefly Algorithm based on Global Optimization) is formed The second one is called FABE (Firefly Algorithm based on Bayesian Estimation) using the optimal moving direction calculated by Bayesian estimation as heuristic information The improved algorithms in this study are applied to numerical simulations of several classical test functions and compared with traditional FA and some other′s research are carried out The simulation results show that the proposed algorithms can well accelerate the convergence speed and improve the convergence accuracy…”
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    Article
  6. 1106

    Optimization method of truss structure size and shape based on harmonic search genetic algorithm by XIE Jun, ZHANG Huashuai, LIN Shuqin, PANG Bolei, YAN Jie

    Published 2025-03-01
    “…Compared with genetic algorithm (GA), heuristic particle swarm optimization (HPSO) and other optimization algorithms, the optimization effect is obvious, and it is a method suitable for the shape optimization of truss structure.…”
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    Article
  7. 1107

    Exploring Evolutionary Algorithms for Multi-Objective Optimization in Seismic Structural Design by Seda Göktepe Körpeoğlu, Süleyman Mesut Yılmaz

    Published 2024-10-01
    “…In particular, evolutionary algorithms such as genetic algorithms and particle swarm optimization are used to optimize the performance of structures to meet seismic loads. …”
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    Article
  8. 1108

    A Comparison of Metaheuristic Algorithms for Structural Optimization: Performance and Efficiency Analysis by Saeedeh Ghaemifard, Amin Ghannadiasl

    Published 2024-01-01
    “…The findings confirm the effectiveness of the algorithms, with particle swarm optimization and social network search frequently delivering superior results across most problem sets.…”
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    Article
  9. 1109
  10. 1110

    Applying the Cheetah Algorithm to optimize resource allocation in the fog computing environment by Fatemeh Arvaneh, Faraneh Zarafshan, Abbas Karimi

    Published 2024-12-01
    “…Preliminary results indicate that the statistical average performance of the Cheetah algorithm surpasses that of the Gray Wolf algorithm, the combined Particle Swarm-Gravitational Search algorithm, and the Gray Wolf-Cuckoo Search algorithm. …”
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    Article
  11. 1111
  12. 1112

    Multi-Class Skin Cancer Classification Using a Hybrid Dynamic Salp Swarm Algorithm and Weighted Extreme Learning Machines with Transfer Learning by Ramya Panneerselvam, Sathiyabhama Balasubramaniam

    Published 2023-04-01
    “…The efficiency of the proposed solution is proved by comparing it with various state-of-the-art approaches such as support vector machine (SVM), ELM, and particle swarm optimization (PSO) methods. Results are evaluated using standard metrics of sensitivity, specificity and precision. …”
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    Article
  13. 1113

    Recent metaheuristic algorithms for solving some civil engineering optimization problems by Essam H. Houssein, Mohamed Hossam Abdel Gafar, Naglaa Fawzy, Ahmed Y. Sayed

    Published 2025-03-01
    “…The performance of the proposed BES–GO algorithm was compared with ten state-of-the-art metaheuristic algorithms: Bald Eagle Search (BES), Growth Optimizer (GO), Ant Lion Optimizer, Tuna Swarm Optimization, Tunicate Swarm Algorithm, Harris Hawk Optimization, Artificial Gorilla Troops Optimizer, Dingo Optimizer, Particle Swarm Optimization, and Grey Wolf Optimizer. …”
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    Article
  14. 1114

    Route Optimization for UGVs: A Systematic Analysis of Applications, Algorithms and Challenges by Dario Fernando Yépez-Ponce, William Montalvo, Ximena Alexandra Guamán-Gavilanes, Mauricio David Echeverría-Cadena

    Published 2025-06-01
    “…Heuristic algorithms, such as Humpback Whale Optimization, Firefly Search and Particle Swarm Optimization, are commonly employed to solve complex search problems. …”
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    Article
  15. 1115

    Adversarial Range Gate Pull-Off Jamming Against Tracking Radar by Yuanhang Wang, Yi Han, Yi Jiang

    Published 2025-03-01
    “…To tackle these challenges, this study formulates the optimization of the RGPO jamming strategy as an adversarial stochastic simulation optimization (ASSO) problem and introduces a novel solution for the white-box RGPO jamming strategy optimization: a local simulation-assisted particle swarm optimization algorithm with an equal resampling scheme (PSO-ER). …”
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    Article
  16. 1116

    Meta-heuristics meet sports: a systematic review from the viewpoint of nature inspired algorithms by Ariyaratne M.K.A., Silva R.M.

    Published 2022-03-01
    “…Some of our findings include (a) genetic algorithm and particle swarm optimization have been extensively used in the literature, (b) meta-heuristics have been widely applied in the sports of cricket and soccer, (c) the limitations and challenges of using meta-heuristics in sports. …”
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    Article
  17. 1117

    Path Optimization of Welding Robot Based on Ant Colony and Genetic Algorithm by Yan Gao, Yiwan Zhang

    Published 2022-01-01
    “…At the same time, the robot with optimized genetic algorithm has smaller fluctuations in joint angle and angular velocity in the simulated welding task, and the optimization algorithm takes 17.6 s less than the traditional particle swarm algorithm and 11 s less than the single A∗ algorithm. …”
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    Article
  18. 1118

    Trajectory Optimization of Hypersonic Periodic Cruise Using an Improved PSO Algorithm by Hesong Li, Yi Wang, Shangcheng Xu, Yunfan Zhou, Dan Su

    Published 2021-01-01
    “…Periodic cruise has the potential to improve the fuel-saving efficiency of hypersonic cruise vehicles but is difficult to optimize. In this paper, hypersonic periodic cruise trajectory is analyzed theoretically and optimized by an improved Particle Swarm Optimization algorithm. …”
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  19. 1119

    Multiobjective Optimization of Copper Coil Blanking Based on Niche Genetic Algorithm by Di He, Xuebing Li, Furong Wei

    Published 2023-01-01
    “…Three algorithms, namely, adaptive particle swarm optimization, niche genetic algorithm based on crowding, and niche genetic algorithm based on seed retention (NGA), were used to solve the problem. …”
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    Article
  20. 1120

    Optimizing Data Classification in Support Vector Machines Using Metaheuristic Algorithms by Qonita Ilmi Awalin, Ika Hesti Agustin, Alfian Futuhul Hadi, Dafik Dafik, R. Sunder

    Published 2024-11-01
    “…To categorize patient diagnosis data related to Chronic Kidney Disease (CKD), this study compares the classification performance of Support Vector Machines (SVM) enhanced by Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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    Article