Multiobjective Optimal Control for Hydraulic Turbine Governing System Based on an Improved MOGWO Algorithm by Xin Xia, Jie Ji, Chao-shun Li, Xiaoming Xue, Xiaolu Wang, Chu Zhang

“…And then, the sMOGWO is applied to optimize the solutions of the multiobjective problems of HTGS, while different algorithms are employed for comparison. …”
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Coverage Optimization Technology of Power Pipe Gallery Based on Improved Gray Wolf Algorithm by Cheng ZHONG, Di ZHAI, Yang LU, Xiaobo LIU, Xinru WANG, Xiongwen ZHAO

“…A comparative simulation analysis is made of various coverage optimization methods, and the results show that the proposed algorithm has robust search capabilities and it can significantly improve the network coverage performance in the narrow underground power pipe galleries, while effectively satisfying the communication needs of the monitored nodes.…”
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Multi-Strategy Improved Harris Hawk Optimization Algorithm and Its Application in Path Planning by Chaoli Tang, Wenyan Li, Tao Han, Lu Yu, Tao Cui

“…First, the double adaptive weight strategy is used to enhance the search capability of the algorithm to significantly improve the convergence accuracy and speed of path planning; second, the Dimension Learning-based Hunting (DLH) search strategy is introduced to effectively balance exploration and exploitation while maintaining the diversity of the population; and then, Position update strategy based on Dung Beetle Optimizer algorithm is proposed to reduce the algorithm’s possibility of falling into local optimal solutions during path planning. …”
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An Improved Particle Swarm Optimization Algorithm forOptimal Allocation of Distributed Generation Units in Radial Power Systems by Neda Hantash, Tamer Khatib, Maher Khammash

“…In this paper, an improved particle swarm optimization method (PSO) is proposed to optimally size and place a DG unit in an electrical power system so as to improve voltage profile and reduce active power losses in the system. …”
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Multi-Objective Optimization for the Low-Carbon Operation of Integrated Energy Systems Based on an Improved Genetic Algorithm by Yao Duan, Chong Gao, Zhiheng Xu, Songyan Ren, Donghong Wu

“…This paper proposes an improved genetic algorithm (IGA) designed to optimize the multi-objective low-carbon operations of IESs, aiming to minimize both operating costs and carbon emissions. …”
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MRP-YOLO: An Improved YOLOv8 Algorithm for Steel Surface Defects by Shuxian Zhu, Yajie Zhou

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Study on Multiobjective Path Optimization of Plant Protection Robots Based on Improved ACO‐DWA Algorithm by Jing Niu, Chuanyan Shen, Lipeng Zhang, Guanghao Gao, Jiahao Zheng

“…To address the false judgment of visual information caused by the shading of branches and leaves and the difficulty in avoiding obstacles in complex orchard terrain, an operation trajectory optimization approach based on the improved dynamic window algorithm (DWA) with ant colony optimization (ACO) was developed. …”
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Improvement teaching-learning-based optimization algorithm for solar cell parameter extraction in photovoltaic systems by H. Khaterchi, M. H. Moulahi, A. Jeridi, R. Ben Messaoud, A. Zaafouri

“…Goal. The work aims to improve the Teaching-Learning-Based Optimization (TLBO) algorithm to enhance the accuracy of parameter extraction in PV models. …”
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AUV path planning method based on improved sparrow search algorithm by Lijun TANG, Yunxia FAN, Xingyu ZHOU, Qian SUN

“…The ISSA also exhibits superior convergence speed, achieving near-optimal paths in approximately 20 iterations, while other algorithms require around 40 iterations to approach the global optimum. …”
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Multi-objective optimization analysis of construction management site layout based on improved genetic algorithm by Hui Yin

“…In construction management, the rationality of on-site layout is crucial for project progress, cost, and safety. In order to improve the rationality of on-site layout, a multi-objective optimization model combining ant colony algorithm and Pareto optimal solution was constructed based on genetic algorithm, and this model was applied to practical engineering cases. …”
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Application of Optimal Scheduling Model Based on Improved Genetic Algorithm in Electric Power Mobile Operation by Rui Fan, Huiying Jing, Zhixin Jing

“…In order to solve the current situation, an optimized scheduling model for power mobile jobs based on improved genetic algorithm is proposed. …”
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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

“…To address the challenges of slow convergence speed, poor convergence precision, and getting stuck in local optima for unmanned aerial vehicle (UAV) three-dimensional path planning, this paper proposes a path planning method based on an Improved Human Evolution Optimization Algorithm (IHEOA). …”
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Improved Coyote Optimization Algorithm for Optimally Installing Solar Photovoltaic Distribution Generation Units in Radial Distribution Power Systems by Thang Trung Nguyen, Thai Dinh Pham, Le Chi Kien, Le Van Dai

“…This paper proposes an improved coyote optimization algorithm (ICOA) for optimizing the location and sizing of solar photovoltaic distribution generation units (PVDGUs) in radial distribution systems. …”
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Coverage optimization of wireless sensor network utilizing an improved CS with multi-strategies by Sen-Yu Yang, Chang-Feng Chen, Kai-Qing Zhou, Yun Ou

“…This makes it well-suited for solving such complex optimization problems. Based on this, this study proposes an improved Cuckoo Search algorithm with multi-strategies (ICS-MS), motivated by the ‘no free lunch’ theorem’s implication that no single optimization strategy universally dominates. …”
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An improved dung beetle optimizer based on Padé approximation strategy for global optimization and feature selection by Tianbao Liu, Lingling Yang, Yue Li, Xiwen Qin

“…This strategy effectively improved the algorithm's ability to jump out of the local optimal and explore potential candidate solutions. …”
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Application of bioinspired global optimization algorithms to the improvement of the prediction accuracy of compact extreme learning machines by L. A. Demidova, A. V. Gorchakov

“…By adjusting input weights with bioinspired optimization algorithms, it was shown that the prediction accuracy of ELMs in regression problems can be improved to reduce the number of hidden-layer neurons to reach a high prediction accuracy on learning and test datasets. …”
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Mixed Multi-Strategy Improved Aquila Optimizer and Its Application in Path Planning by Tianyue Bao, Jiaxin Zhao, Yanchang Liu, Xusheng Guo, Tianshuo Chen

“…Comparative analysis with seven other optimization algorithms reveals that the proposed method significantly improves both convergence speed and optimization accuracy. …”
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Control Strategy of a Rotating Power Flow Controller Based on an Improved Hybrid Particle Swarm Optimization Algorithm by Ziyang Zhang, Jiaoxin Jia, Waseem Aslam, Abubakar Siddique, Fahad R. Albogamy

“…Notably, this paper introduces intelligent optimization algorithms to this field for the first time, employing an improved hybrid particle swarm optimization (HPSO) algorithm to control the active power while keeping the reactive power constant and subsequently adjusting the reactive power while maintaining the active power steady, thereby achieving power regulation. …”
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Improved optimization based on parrot’s chaotic optimizer for solving complex problems in engineering and medical image segmentation by Adil Sayyouri, Ahmed Bencherqui, Hanaa Mansouri, Hicham Karmouni, Hassane Moustabchir, Mhamed Sayyouri, Abderrahim Bourkane, Abdeljabbar Cherkaoui, S. S. Askar, Mohamed Abouhawwash

“…A recent algorithm, the Parrot Optimizer (PO), is inspired by the behavior of domestic parrots to improve the diversity of solutions. …”
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An Improved Multi-Objective Adaptive Human Learning Optimization Algorithm and Its Application in Optimizing Formulation Schemes for Rotary Hearth Furnaces by Jun Yao, Songcheng Zhou, Ling Wang, Xianxia Zhang

“…An improved multi-objective adaptive human learning optimization algorithm (IMOAHLO) is proposed, which enhances local optimization through neighborhood search and an adaptive learning mechanism. …”
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