基于和声搜索和模式探测移动的混沌鱼群算法  

Chaotic fish swarm algorithm based on harmony search and movement of mode detection

作　　者：杨晓龙[1] 李林[1] 

机构地区：[1]上海理工大学管理学院,上海200093

出　　处：《信息技术》2015年第1期29-33,共5页Information Technology

基　　金：国家自然科学基金项目(70971089);上海市重点学科建设资助项目(S30501)

摘　　要：鱼群算法是一种群智能优化算法,寻优效果良好,但后期易产生陷入局部极值;混沌搜索全局搜索能力强,能跳出局部极值,但局部搜索能力不强。为了提高算法的全局搜索能力和搜索精度,文中提出一种基于和声搜索和模式探测移动的混沌鱼群算法,在鱼群寻优过程中利用混沌搜索的遍历性使其摆脱局部极值,同时用模式探测移动、和声搜索来提高搜索精度。仿真结果表明,该算法比基本鱼群算法和混沌鱼群算法的搜索精度更高,收敛速度更快。Fish swarm algorithm is a swarm intelligent algorithm of optimization, has good results of optimization, but the later is easy to fall into local extremum. The chaotic search has the strong ability of searching globally, can jump out the local extremum, but the fine search ability is not strong. In order to improve the algorithm＇s global searching ability and the accuracy of search, the article gives out a chaotic fish swarm algorithm based on harmony search and movement of mode detection, uses the ergodicity of chaotic search to make the fish jump out the local extremum after the optimizing process of fish swarm, then uses the movement of mode detection, harmony search to improve the accuracy of the search. The simulation results show that the algorithm has a higher searching accuracy and a faster convergence speed than the basic fish swarm algorithm and chaotic fish swarm algorithm.

关 键 词：鱼群算法 混沌搜索 模式探测移动 和声搜索 局部极值 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]