Optimisation Algorithm for Slime Moulds based on Improved Multi-strategy Fusion
SONG Yadi1**,WANG Haibo1*,ZHAO Chuanzhe1**,WANG Ronglin1***，LI Zhifeng2****,Li Pengtao2***
(1.School of Mechanical and Electrical Engineering, Jilin Institute of Chemical Technology, Jilin City 132022,China；2.School of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin City, 132022,China)
Abstract: Aiming at the problems of slow convergence speed, difficult parameter selection and easy to fall into local optimal solutions of the slimy mushroom optimisation algorithm (SMA), a multi-strategy fusion improved slimy mushroom optimisation algorithm (LTSSMA) is proposed. The Latin hypercube is used to optimise the population initialisation; the position of the population particles is perturbed using the adaptive t-distribution variation to improve the convergence speed of the algorithm; the positive cosine optimisation strategy is introduced and the adaptive weight improvement is performed to reduce the probability of the algorithm falling into the local optimal solution. The improved algorithm is tested using the CEC2005 test function, and through the analysis of the obtained images and data, it is obtained that the improved mucilage optimisation algorithm has improved in convergence speed and the ability to get rid of the local optimal solution.
宋亚迪, 王海波, 赵传哲, 王荣林, 李志锋, 李鹏涛. 多策略融合改进的黏菌优化算法[J]. 吉林化工学院学报, 2024, 41(9): 62-69.
SONG Yadi, WANG Haibo, ZHAO Chuanzhe, WANG Ronglin, LI Zhifeng, Li Pengtao . Optimisation Algorithm for Slime Moulds based on Improved Multi-strategy Fusion. Journal of Jilin Institute of Chemical Technology, 2024, 41(9): 62-69.
