计算机与数字工程2025，Vol.53Issue(2)：308-313,357,7.DOI:10.3969/j.issn.1672-9722.2025.02.003
多种策略改进的黏菌算法
Improved Slime Mold Algorithm with Multiple Strategies
摘要
Abstract
The slime mold algorithm is easy to fall into local optimal stagnation and slow convergence speed,so an improved slime mold algorithm based on a variety of hybrid strategies is proposed.Firstly,the chaotic map is used to initialize the population and increase the diversity of the population.The global exploration and local development ability of the adaptive adjustable feedback factor coordination algorithm is introduced into the updating position of myxomycetes.The random learning strategy in the teaching and learning optimization algorithm is combined with the slime mold algorithm to avoid the blind optimization in the global algo-rithm.The mutation operation of Lévy flight mutation mechanism makes the algorithm jump out of local optimum.The performance of the improved algorithm is tested on eight standard test functions.The results show that the improved algorithm is robust,precise and fast.The classical optimization problem of truss structure is solved by the algorithm,which is superior to other algorithms in the opti-mization design of truss structure and runs fewer iterations to reach the objective function.关键词
黏菌算法/混沌映射/反馈因子/随机学习策略/莱维飞行/测试函数/桁架优化Key words
slime molds algorithm/chaotic map/back feed factor/random learning strategy/Lévy flight/test function/truss optimization分类
建筑与水利引用本文复制引用
王晓磊,庞娜,刘历波..多种策略改进的黏菌算法[J].计算机与数字工程,2025,53(2):308-313,357,7.基金项目
中国国家自然青年科学基金项目(编号:51708317)资助. （编号:51708317）
