首页|A Multi-strategy Improved Snake Optimizer Assisted with Population Crowding Analysis for Engineering Design Problems

A Multi-strategy Improved Snake Optimizer Assisted with Population Crowding Analysis for Engineering Design Problems

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Snake Optimizer(SO)is a novel Meta-heuristic Algorithm(MA)inspired by the mating behaviour of snakes,which has achieved success in global numerical optimization problems and practical engineering applications.However,it also has certain drawbacks for the exploration stage and the egg hatch process,resulting in slow convergence speed and inferior solution quality.To address the above issues,a novel multi-strategy improved SO(MISO)with the assistance of population crowding analysis is proposed in this article.In the algorithm,a novel multi-strategy operator is designed for the exploration stage,which not only focuses on using the information of better performing individuals to improve the quality of solution,but also focuses on maintaining population diversity.To boost the efficiency of the egg hatch process,the multi-strategy egg hatch process is proposed to regenerate individuals according to the results of the population crowding analysis.In addition,a local search method is employed to further enhance the convergence speed and the local search capability.MISO is first compared with three sets of algorithms in the CEC2020 benchmark functions,including SO with its two recently discussed variants,ten advanced MAs,and six powerful CEC competition algorithms.The performance of MISO is then verified on five practical engineering design problems.The experimental results show that MISO provides a promising performance for the above optimization cases in terms of convergence speed and solution quality.

Snake optimizerMulti-strategyPopulation crowding analysisEngineering design problem

Lei Peng、Zhuoming Yuan、Guangming Dai、Maocai Wang、Jian Li、Zhiming Song、Xiaoyu Chen

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School of Computer Science,China University of Geosciences,Wuhan 430074,China

Hubei Key Laboratory of Intelligent Geo-Information Processing,China University of Geosciences,Wuhan 430074,China

China Astronautics Standards Institute,Beijing 100071,China

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaJoint Funds of Equipment Pre-Research and Ministry of Education of ChinaSpecial Project of Hubei Key Research and Development ProgramOpen Research Project of the Hubei Key Laboratory of Intelligent Geo-Information Processing

42271391620062148091B0221482023BIB015KLIGIP-2021B03

2024

10.1007/s42235-024-00505-7

仿生工程学报(英文版)
吉林大学

仿生工程学报(英文版)

CSTPCDEI
影响因子：0.837
ISSN：1672-6529
年,卷(期)：2024.21(3)
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