基于觅食生境选择的改进粒子群算法  

Improved Particle Swarm Optimization Based on Feeding Habitat Selection

作　　者：陈子廓 史宪睿 CHEN Zi-kuo;SHI Xian-rui(School of Economics and Management,Liaoning University of Technology,Jinzhou 121001,China)

机构地区：[1]辽宁工业大学经济管理学院,辽宁锦州121001

出　　处：《辽宁工业大学学报（自然科学版）》2022年第1期19-21,共3页Journal of Liaoning University of Technology(Natural Science Edition)

摘　　要：在标准粒子群算法的基础上,引入基于莱维飞行的觅食生境选择策略,提出了改进的基于觅食生境选择的粒子群算法(feeding habitat selection particle swarm optimization,FHSPSO)。改进的算法中,粒子搜索策略包括粒子无干扰觅食和受到惊扰飞至新的觅食位置两个阶段。应用6个典型的高维标准测试函数对算法进行测试,结果表明,FHSPSO算法的性能相对标准粒子群算法有很大提升。On the basis of standard particle swarm algorithm,the strategy of feeding habitat selection based on Levy Flight is introduced,and the swarm algorithm based on feeding habitat selection particle swarm optimization is come up with(FHSPSO).In the improved algorithm,the strategy of looking for swarms includes two stages,one is that the swarms forage without interference,the other is that the swarms fly to a new foraging position after they are disturbed.Six typical high dimensional standard test functions are used to test the algorithm.The conclusion shows the functions of FHSPSO algorithm obtain much more improvements than the standard particle swarm algorithm.

关 键 词：粒子群算法 莱维飞行 觅食生境选择 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]