Maximum likelihood DOA estimation based on improved ant colony optimization algorithm by JIAO Yameng, LI Wenping, WU Yue, CUI Lin

“…Simulation results show that, compared with ML estimation methods based on particle swarm optimization (PSO) algorithm and ACO algorithm, the convergence speed of the ML-MACO algorithm is 4 times faster than that of the ML-ACO algorithm, the computational load is 1/3 that of the ML-ACO algorithm, the resolution success rate is higher than the ML-PSO algorithm and the ML-ACO algorithm, and the estimation error is less than the ML-PSO algorithm and the ML-ACO algorithm. …”
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Queueing modeling and optimization of hybrid electric vehicle infrastructures using evolutionary algorithms by Shreekant Varshney, Manthan Shah, Bhasuru Abhinaya Srinivas, Mayank Gupta, Kaibalya Prasad Panda

“…The novelty of the proposed research is to formulate the cost optimization problem and demonstrate optimal converging outcomes through an in-depth comparative investigation of multiple evolutionary algorithms, including the particle swarm optimization (PSO), cuckoo search (CS), grey wolf (GW), and honey badger (HB) optimizers. …”
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Evaluating the Nuclear Reaction Optimization (NRO) Algorithm for Gene Selection in Cancer Classification by Shahad Alkamli, Hala Alshamlan

“…Comparative analysis with Harris Hawks Optimization (HHO), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), and Firefly Algorithm (FFA) shows that while NRO delivers competitive performance, it does not consistently outperform all methods across datasets. …”
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Optimizing Photovoltaic Panel Performance: A Comparative Study of Meta-Heuristic Algorithms by M. Sundar Rajan

“…This paper addresses the parameter estimation of four distinct PV panel models—PV-RTC, PV-PWP 201, PV-STM6 40/36, and PV-STP6 120/36—using a range of meta-heuristic optimization algorithms. The centerpiece of this study is the introduction of a novel hybrid algorithm, HPSGWO, which combines Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO) techniques. …”
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Evaluation of the Efficiency of Metaheuristic Algorithms in the Optimal Design of Pile Wall Retaining Systems by Farshad Taiyari

“…Four different metaheuristic algorithms, namely Genetic, Particle swarm optimization, Bee, and Biogeography-based algorithms, are chosen for the optimization problem. …”
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Predicting the Classification of Heart Failure Patients Using Optimized Machine Learning Algorithms by Marzia Ahmed, Mohd Herwan Sulaiman, Md Maruf Hassan, Touhid Bhuiyan

“…This study proposes an optimized machine learning approach using Gradient Boosting Machine (GBM) and Adaptive Inertia Weight Particle Swarm Optimization (AIW-PSO) to predict heart failure survival. …”
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Comparative Analysis of Optimization Algorithms to Enhance WPGSs Performance: Malaysia Case Study by Hussein Shutari, Taib Ibrahim, Nursyarizal Bin Mohd Nor, Hakim Abdulrab, Yahya Z. Alharthi, Mohammad Faridun Naim Tajuddin, Maveeya Baba

“…The growing interest in wind power and its expanding integration into the electrical power grid necessitate significant efforts to enhance the efficiency and performance of wind power generation Systems (WPGS) through optimized design and operation. This paper investigates the implementation of five optimization algorithms:sine cosine algorithm (SCA), grey wolf optimizer (GWO), particle swarm optimizer (PSO), transient search optimization (TSO), and a hybrid sine cosine algorithm-transient search optimizer (HSCATSO), to optimally design control schemes (ODCSs) of frequency converters within grid-connected WPGS. …”
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Path Scheduling and Target Trajectory Optimization in UAVs Based on Dragonfly and Firefly Algorithm by Methaq Hadi Lafta

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Application of Improved Whale Algorithm to Optimize Dephosphorization Process Parameters in Converter Steelmaking by Congrui Wu, Yueping Kong

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Path Planning of UAV Using Levy Pelican Optimization Algorithm In Mountain Environment by Guiliang Zhou, Shuaiqi Lü, Lina Mao, Kaiwen Xu, Tianwen Bao, Xu Bao

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An innovative complex-valued encoding black-winged kite algorithm for global optimization by Chengtao Du, Jinzhong Zhang, Jie Fang

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Black Hole Algorithm for Software Requirements Prioritization by Norah Ibrahim Alfassam, M. Abdullah-Al-Wadud, Mubarak Rashed Alrashoud

“…Furthermore, the proposed BHA-based solution was evaluated on three real-world datasets (RALIC, Word, and ReleasePlanner), and its performance was compared with that of multiple state-of-the-art algorithms, including Ant Colony Optimization (ACO), Genetic Algorithm (GA), Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Fitness Dependent Optimizer (FDO), Goose Algorithm (GAO), and Lagrange Elementary Optimization (LEO). …”
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Improved Bald Eagle Search Optimization Algorithm for the Inverse Kinematics of Robotic Manipulators by Guojun Zhao, Bo Tao, Du Jiang, Juntong Yun, Hanwen Fan

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Sustainable closed-loop supply chain network planning considering price competition using particle chaotic ant colony algorithm by Tianrui Zhang, Quanfeng He, Weibo Zhao, Mingqi Wei

“…Thirdly, the problems of premature convergence and slow convergence during the traditional particle swarm optimization algorithm and genetic algorithm are solved with the particle chaotic ant colony algorithm (PSCACO). …”
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Research on Capacitated Multi-Ship Replenishment Path Planning Problem Based on the Synergistic Hybrid Optimization Algorithm by Lin Yang, Qinghua Chen, Junjie Mu, Tangying Liu, Xiaoxiao Li, Shuxiang Cai

“…To evaluate performance, the SHOA is benchmarked against ACO, the GA, the particle swarm optimization algorithm, and the simulated annealing algorithm for the capacitated vehicle routing problem. …”
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A Bi-Objective Optimal Scheduling Method for the Charging and Discharging of EVs Considering the Uncertainty of Wind and Photovoltaic Output in the Context of Time-of-Use Electrici... by Xinfu Pang, Wen Jia, Haibo Li, Qingzhong Gao, Wei Liu

“…Finally, the model was solved using an improved multi-objective barebones particle swarm optimization algorithm. The simulation results show that the proposed scheduling strategy has a lower charging cost (CNY 11,032.4) and lower load mean square error (12.84 × 10⁵ kW²) than the strategy employed in the comparison experiment, which ensures the economic and stable operation of the microgrid.…”
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Design of Cloud-Based Complex VR 3D Scene Interaction Based on Attribute Preferences by Ze Yu Yang, Yeom Jun Young

“…The study leverages Reinforcement Learning (RL) and Particle Swarm Optimization (PSO) to address critical challenges such as user interface adaptability and cloud resource allocation. …”
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Optimizing Deep Learning Models with Improved BWO for TEC Prediction by Yi Chen, Haijun Liu, Weifeng Shan, Yuan Yao, Lili Xing, Haoran Wang, Kunpeng Zhang

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Progress in Construction Robot Path-Planning Algorithms: Review by Shichen Fu, Detao Yang, Zenghui Mei, Weixiong Zheng

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A systematic review on search‐based test suite reduction: State‐of‐the‐art, taxonomy, and future directions by Amir Sohail Habib, Saif Ur Rehman Khan, Ebubeogu Amarachukwu Felix

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