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A Multi-strategy Improved Snake Optimizer Assisted with Population Crowding Analysis for engineering design problems

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Journal of Bionic engineering 2024年第3期21卷 1567-1591页

作者： Lei Peng Zhuoming Yuan Guangming Dai Maocai Wang Jian Li Zhiming Song Xiaoyu Chen School of Computer Science China University of GeosciencesWuhan430074China Hubei Key Laboratory of Intelligent Geo-Information Processing China University of GeosciencesWuhan430074China China Astronautics Standards Institute Beijing100071China

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 ***,it also has certain drawbacks for the exploration stage and the egg hatch process,resulting in slow convergence speed and inferior solution *** address the above issues,a novel multi-strategy improved SO(MISO)with the assistance of population crowding analysis is proposed in this *** 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 *** 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 *** addition,a local search method is employed to further enhance the convergence speed and the local search *** 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 *** performance of MISO is then verified on five practical engineering design *** experimental results show that MISO provides a promising performance for the above optimization cases in terms of convergence speed and solution quality.

关键词： Snake optimizer Multi-strategy Population crowding analysis engineering design problem

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