计算机工程与科学2024，Vol.46Issue(4)：693-706,14.DOI:10.3969/j.issn.1007-130X.2024.04.014
基于混合策略改进的蛇优化算法及其应用
An improved snake optimization algorithm based on hybrid strategies and its application
摘要
Abstract
To solve the problem that the basic snake optimization algorithm easily falls into local op-timization,an improved snake optimization algorithm(SSO)based on dimension selection strategy,se-lection mating strategy,and re-grouping strategy is proposed.The SSO algorithm introduces the dimen-sion selection strategy in the combat or mating stage of the basic snake optimization algorithm.The ran-dom probability is used to select the position update mode of each snake individual in different dimen-sions,so as to avoid the phenomenon of individual position stagnation in the later stage of iteration.The selection mating strategy is introduced in the combat or mating stage,and a part of individuals with smaller fitness values are selected for combat or mating.The remaining individuals use the exploration stage position update formula for position update to improve the exploration ability of the combat or mating stage.The re-grouping strategy is used,and the individuals are randomly disrupted and re-grouped every ten iterations to increase population diversity and improve the optimization ability of the algorithm.Numerical experiments on 30 standard unconstrained optimization problems show that com-pared with six comparative algorithms such as the basic snake optimization algorithm SO,the SSO algo-rithm has stronger optimization ability and is more effective for solving high-dimensional optimization problems.The SSO algorithm is used to optimize the initial weights and thresholds of BP neural net-works.Experimental results show that the SSO-BP neural network has better accuracy and stability than other comparative neural networks in classifying wines and predicting abalone age.关键词
蛇优化算法/维度选择策略/选择交配策略/重新分组策略/数值实验Key words
snake optimization algorithm/dimension selection strategy/selection mating strategy/re-grouping strategy/numerical experiment分类
信息技术与安全科学引用本文复制引用
梁昔明,史兰艳,龙文..基于混合策略改进的蛇优化算法及其应用[J].计算机工程与科学,2024,46(4):693-706,14.基金项目
国家自然科学基金(12361106) （12361106）
贵州省自然科学基金重点项目(黔科合基础-ZK[2003]重点003) （黔科合基础-ZK[2003]重点003）
中央支持地方科研创新团队项目(PXM2013_014210_000173) （PXM2013_014210_000173）
北京建筑大学2021年校级教育科学研究项目(Y2113) （Y2113）
