Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm by Xiaoshi Zhuang, Honglue Wan, Dongran Song, Xinyu Fan, Yuchen Wang, Qian Huang, Jian Yang

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Improved PESA algorithm based on comentropy by Kun WANG, Lin-lin WANG, Yan LIU, Yu-hua ZHANG, Meng WU

“…Simula-tion results show that the computational effort of C-PESA increases linearly with the rising number of solutions. Mean-while, the computation time is improved almost four times, and the evolutionary computation efficiency is also enhanced.…”
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Optimization of Jaw Crusher Based on Improved Genetic Algorithm by SUN Yu-fei, ZHENG Xiao-wen, CHEN Hao, LIU Xiao-Shan

“…Aiming at the deficiency of ANSYS′s own optimization algorithm, the improved genetic algorithm is applied to the structural optimization design of ANSYS.Taking the whole structure optimization of jaw crusher as an example, the optimization platform of jaw crusher based on SolidWorks and ANSYS is established.The traditional optimization algorithm of ANSYS and the improved genetic algorithm with embedded ANSYS finite element analysis are used to optimize the design.The results show that compared with the optimization algorithm of ANSYS, the improved genetic algorithm has obvious advantages in the overall structure design of jaw crusher. …”
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Application of improved particle swarm optimization algorithm combined with genetic algorithm in shear wall design by Wei Gao

“…The improved algorithm is based on the basic framework of genetic algorithm and particle swarm optimization algorithm, first adjusting the inertia weight, and then introducing elimination mechanism and mutation rate control. …”
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Improved grey wolf optimization algorithm based service function chain mapping algorithm by Yue ZHANG, Junnan ZHANG, Xiaochun WU, Chen HONG, Jingjing ZHOU

“…With the rise of new Internet applications such as the industrial Internet, the Internet of vehicles, and the metaverse, the network’s requirements for low latency, reliability, security, and certainty are facing severe challenges.In the process of virtual network deployment, when using network function virtualization technology, there were problems such as low service function chain mapping efficiency and high deployment resource overhead.The node activation cost and instantiation cost was jointly considered, an integer linear programming model with the optimization goal of minimizing the average deployment network cost was established, and an improved grey wolf optimization service function chain mapping (IMGWO-SFCM) algorithm was proposed.Three strategies: mapping scheme search based on acyclic KSP algorithm, mapping scheme coding and improvement based on reverse learning and nonlinear convergence were added to the standard grey wolf optimization algorithm to form this algorithm.The global search and local search capabilities were well balanced and the service function chain mapping scheme was quickly determined by IMGWO-SFCM.Compared with the comparison algorithm, IMGWO-SFCM reduces the average deployment network cost by 11.86% while ensuring a higher service function chain request acceptance rate.…”
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Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm. by Xiaotong Bai, Yuefeng Zheng, Yang Lu, Yongtao Shi

“…In particular, the wrapper algorithm is an improved Grey Wolf Optimization (IGWO) algorithm based on random disturbance factors, while the parameters are adjusted to vary randomly to make the population variations rich in diversity. …”
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Microservice combination optimisation based on improved gray wolf algorithm by Jingjing Hu, Xiaojun Xu, Jin Hao, Xiuqi Yang, Kefan Qiu, Yuanzhang Li

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An Improved Coral Reef Optimization-Based Scheduling Algorithm for Cloud Computing by Shuzhen Wan, Lixin Qi

“…In this paper, we establish a resource allocation framework and propose a novel task scheduling algorithm. An improved coral reef optimization (ICRO) is proposed to deal with this task scheduling problem. …”
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A multistrategy improved hunger games search algorithm by Qiu Yihui, Zhang Xinqiang, Li Ruoyu, Li Dongyi, Xia Feihan

“…Abstract In this paper, we propose a multistrategy improved Hunger Games Search (MHGS) algorithm to address several inherent limitations of the original HGS, including imbalanced exploration and exploitation, insufficient population diversity, and premature convergence. …”
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A Multi-Strategy Improved Horned Lizard Optimization Algorithm and Its Application in Engineering Optimization by Yancang Li, Jinfan Zhang, Zidong Jin, Weitao Qiao

“…In this study, a multi-strategy improved horned lizard optimization algorithm (MSHLOA) is proposed to overcome the limitations of the standard HLOA in terms of premature convergence and slow optimization search. …”
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An Improved Convergence Particle Swarm Optimization Algorithm with Random Sampling of Control Parameters by Lijun Sun, Xiaodong Song, Tianfei Chen

“…The final experiments results demonstrate that the proposed algorithm further improves the convergence rate while maintaining higher convergence accuracy, compared with basic particle swarm optimization and other variants.…”
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Improved Trimming Ant Colony Optimization Algorithm for Mobile Robot Path Planning by Junxia Ma, Qilin Liu, Zixu Yang, Bo Wang

“…To address these challenges, this paper proposes an improved trimming ant colony optimization (ITACO) algorithm. …”
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Application of Improved Whale Algorithm to Optimize Dephosphorization Process Parameters in Converter Steelmaking by Congrui Wu, Yueping Kong

“…This study addresses process parameter optimization challenges in converter steelmaking by proposing an improved multi-objective whale optimization algorithm (IMOWOA) that synergistically integrates metallurgical thermodynamics with data-driven modeling. …”
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AOAFS: A Malware Detection System Using an Improved Arithmetic Optimization Algorithm by Rafat Alshorman, Bilal H. Abed-alguni, Yaqeen E. Alqudah

“…Finally, Dynamic Opposition-based Learning is utilized to improve the mutation capability of the AOAFS. Several malware datasets were used to compare the AOAFS to four popular Machine Learning algorithms and eight famous wrapper-based optimization algorithms. …”
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Multi-objective Path Planning for AUVs Based on Improved Whale Optimization Algorithms and Fluid Disturbance Algorithms by Yuhong MA, Wen PANG, Daqi ZHU

“…Simulation results demonstrate that the proposed algorithm reduces the average path length by 15.4% and 7.5% compared to traditional genetic algorithm and particle swarm optimization, respectively, while improving computational efficiency by 45.5% and 16.8%.…”
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MULTI-OBJECTIVE OPTIMIZATION DESIGN FOR CUTTING MECHANISM OF ROADHEADER BASED ON IMPROVED GENETIC ALGORITHM by MAO Jun, PAN DeWen, XIE Miao, ZHENG GuangHui

“…This paper takes motion parameters and structure parameters of cutting mechanism for design variables and optimizes multi-objective function of comprehensive performance of cutting mechanism based on the improved genetic algorithm. …”
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Research on Multi-Center Path Optimization for Emergency Events Based on an Improved Particle Swarm Optimization Algorithm by Zeyu Zou, Hui Zeng, Xiaodong Zheng, Junming Chen

“…Experimental findings underscore the potential of the proposed approach in optimizing emergency response logistics. The hybrid algorithm consistently achieves significant reductions in total cost while maintaining fairness in material distribution. …”
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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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Optimizing aerodynamic shape of benchmark problems using an improved Gaussian process regression algorithm by Youtao Xue, Yuxin Yang, Shaobo Yao, Wenwen Zhao, Lihua Chen

“…Compared to the conventional GPR-based SBO approach, our AKC-GPR framework significantly reduces the number of required computational fluid dynamics (CFD) simulations by 27.7% while improving drag reduction by 2.83%. Qualitative and approximate comparative analysis of the results with other research groups on the same benchmark case validates the robustness and effectiveness of our proposed optimization framework.…”
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An Improved NSGA-II Algorithm for Multi-Objective Optimization of Irregular Polygon Patch Antennas by Zhenyang Ma, Jiahao Liu

“…This paper presents an improved NSGA-II algorithm for the multi-objective optimization of irregular polygon patch antennas (IPPAs), improving convergence efficiency and Pareto front quality. …”
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