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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Integration of electric vehicle charging stations with distributed generation using multi-objective metaheuristic optimization by Aya Desoky Gaber, E.M. Abdallah, M.I. Elsayed, Ahmed Abdelbaset

“…This paper uses a multi-objective optimization approach metaheuristic algorithm, specifically the Whale Optimization Algorithm (WOA), Zebra Optimization Algorithm (ZOA), and Puma Optimization Algorithm (POA), to determine the optimal size and placement of DG units in the presence of EVCS. …”
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RESEARCH ON THE REMAINING INTENSITY OF PIPELINE CORROSION BASED ON IWOA-LSSVM by ZHANG Jia, Ll LinFeng, WANG HaoJie, ZHANG Ting

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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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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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Next-Generation energy Management: Particle Density algorithm for residential microgrid optimization by Liang Wang, Nan Sun

“…The improved particle swarm optimization (IPSO) algorithm is employed to optimize energy management, resolve convergence challenges, and ensure user requirements are effectively prioritized. …”
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Hybrid Improved PSO Algorithm for Soil Property Parameter Estimation by Mude Li, Aiping Shi, Yefan Shi, Tao Zhang, Cu Qu, Lihua Ye

“…For multimodal functions (e.g., F3), PSO-EDO significantly outperforms PSO-WOA (Particle Swarm Optimization-Whale Optimization Algorithm) with a 22.3% reduction in error. …”
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Advanced Optimization Methods for Nonlinear Backstepping Controllers for Quadrotor-Slung Load Systems by Muhammad Maaruf, Sulaiman S. Ahmad, Waleed M. Hamanah, Abdullah M. Baraean, Md Shafiul Alam, Mohammad A. Abido, Md Shafiullah

“…Then the formulated optimization problem is then solved by employing two efficient metaheuristic algorithms, the improved grey wolf optimizer (IGWO) and the whale optimization algorithm (WOA). …”
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Low-Power Intelligent Wireless Sensor Network for Precision Agriculture Oriented Agricultural Greenhouse Management System by Hongguo Jin

“…When the number of sensor nodes was 100, the improved whale optimization algorithm accounted for only 15% of the routing energy consumption, while the simulated annealing algorithm accounted for 53% of the routing energy consumption. …”
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Hybrid Attention-Enhanced Xception and Dynamic Chaotic Whale Optimization for Brain Tumor Diagnosis by Aliyu Tetengi Ibrahim, Ibrahim Hayatu Hassan, Mohammed Abdullahi, Armand Florentin Donfack Kana, Amina Hassan Abubakar, Mohammed Tukur Mohammed, Lubna A. Gabralla, Mohamad Khoiru Rusydi, Haruna Chiroma

“…The methodology is built on a combination of preprocessing techniques, transfer learning architecture reconstruction, and dynamic fine-tuning strategies. To optimize key hyper-parameters, this study employed the Dynamic Chaotic Whale Optimization Algorithm. …”
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Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

“…Aiming at the problems of low accuracy and low efficiency of traditional soil water content prediction methods, support vector machine (SVM) was used to establish a prediction model, and the soil water content prediction method based on SVM optimized was proposed by the improved salp swarm algorithm.Firstly, the opposition-based learning and chaotic optimization were introduced to improve the standard salp swarm algorithm to solve the problem that the algorithm was easy to fall into the local optimal solution and its convergence speed was slow.Secondly, the improved salp swarm algorithm was used to optimize the parameters that affect the performance of SVM and the corresponding prediction model was built.Finally, the proposed model was compared with the particle swarm optimization SVM and the whale algorithm optimized SVM prediction model.The experimental results show that the mean square error and decision coefficient of the proposed model are 0.42 and 0.901, which are better than the other two models which verified the effectiveness of the proposed method.…”
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Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

“…Aiming at the problems of low accuracy and low efficiency of traditional soil water content prediction methods, support vector machine (SVM) was used to establish a prediction model, and the soil water content prediction method based on SVM optimized was proposed by the improved salp swarm algorithm.Firstly, the opposition-based learning and chaotic optimization were introduced to improve the standard salp swarm algorithm to solve the problem that the algorithm was easy to fall into the local optimal solution and its convergence speed was slow.Secondly, the improved salp swarm algorithm was used to optimize the parameters that affect the performance of SVM and the corresponding prediction model was built.Finally, the proposed model was compared with the particle swarm optimization SVM and the whale algorithm optimized SVM prediction model.The experimental results show that the mean square error and decision coefficient of the proposed model are 0.42 and 0.901, which are better than the other two models which verified the effectiveness of the proposed method.…”
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Research on Springback Compensation Method of Roll Forming Based on Improved Fuzzy PID Control by Tengqiang Wang, Yingping Qian, Wengkang Fang, Dongqiao Zhang, Huanqi Weng, Yiran Jiang

“…To realize the precise control required by the springback compensation control strategy, a fuzzy PID controller strategy optimized by the coupled whale particle (CWP) algorithm is designed. …”
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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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Multi-objective optimization analysis of construction management site layout based on improved genetic algorithm by Hui Yin

“…The results show that in terms of computational time, the genetic algorithm takes an average of 1702.0 s, while the improved algorithm takes an average of 421.0 s, which is 1281s less and 85.9% more than before the improvement. …”
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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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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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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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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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