多种策略改进的黏菌算法  

Improved Slime Mold Algorithm with Multiple Strategies

作　　者：王晓磊[1] 庞娜 刘历波[1] WANG Xiaolei;PANG Na;LIU Libo(School of Civil Engineering,Hebei University of Engineering,Handan 056107)

机构地区：[1]河北工程大学土木工程学院,邯郸056107

出　　处：《计算机与数字工程》2025年第2期308-313,357,共7页Computer & Digital Engineering

基　　金：中国国家自然青年科学基金项目(编号:51708317)资助。

摘　　要：针对黏菌算法易陷入局部最优停滞,收敛速度慢等问题,提出了基于多种混合策略改进的黏菌算法。首先采用混沌映射初始化种群,增加种群的多样性;在黏菌个体更新位置引入自适应可调节反馈因子协调算法的全局探索与局部开发能力;将教与学优化算法中的随机性学习策略与黏菌算法结合,避免算法在全局的盲目寻优;利用Lévy飞行的变异机制的变异操作,使得算法跳出局部最优。对八个标准的测试函数对改进算法进行寻优性能测试,结果表明,改进后的算法鲁棒性强,寻优精度强,寻优速度快。选取了经典的桁架结构优化问题用算法进行求解,该算法在桁架结构优化设计中优于其他算法,运行更少的迭代次数达到目标函数。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 

分 类 号：TU323.4[建筑科学—结构工程]