纺织高校基础科学学报2018，Vol.31Issue(1)：115-121,7.DOI:10.13338/j.issn.1006-8341.2018.01.019
基于Levy变异的反向粒子群优化算法
Opposition-based particle swarm optimization based on Levy variation
摘要
Abstract
In order to balance the global search and local search performance of particle swarm algorithm,overcome the disadvantage of easy to fall into local extremum,a method of opposi-tion-based particle swarm optimization based on Levy variation is proposed.The algorithm a-dopts the opposition-based learning strategy and an improved search strategy with Levy flight characteristics,and uses the position factor and speed factor to judge the stagnant particles. Then six typical benchmark functions are used to compare the search results of the new algo-rithm with the standard particle swarm algorithm and opposition-based particle swarm algo-rithm,the results show that the new algorithm is superior to the other two algorithms in the early search capability and the later search precision.关键词
局部极值/反向学习/Levy飞行特征/停滞Key words
local extremum/opposition-based learning/Levy flight characteristics/stagnation分类
轻工纺织引用本文复制引用
南杰琼,王晓东..基于Levy变异的反向粒子群优化算法[J].纺织高校基础科学学报,2018,31(1):115-121,7.基金项目
陕西省自然科学基金(2016JM1031) （2016JM1031）
