具有合作策略的粒子群优化算法  

Particle Swarm Optimizer with Cooperative Search Strategy

作　　者：陈永刚 刘宇建[1] 王招雨 CHEN Yonggang;LIU Yujian;WANG Zhaoyu(College of Information Technology,Xuchang University,Xuchang 461000,China;Yuzhou Senior High School,Yuzhou 461670,China)

机构地区：[1]许昌学院信息工程学院,河南许昌461000 [2]禹州市高级中学,河南禹州461670

出　　处：《许昌学院学报》2023年第2期101-106,共6页Journal of Xuchang University

基　　金：河南省高等学校重点科研项目(20B520033)。

摘　　要：提出了一种具有合作搜索策略的粒子群优化算法(PSOCS).PSOCS的想法受到了生物种群中的角色划分和合作的启发.在PSOCS中,所有粒子被分成两个群.在这两个群中使用了不同的搜索策略,一个子群具有较好开采能力,另一个子群具有较好的探索能力.为了确保这两个子群之间更好的协作搜索,PSOCS中采用了一个变异策略.该变异策略更好体现了两个子群之间的信息交流.为了测试PSOCS的性能,选择了几个标准函数进行了数值实验.实验结果表明,与其他几个粒子群算法相比,PSOCS在求解质量和可靠性方面具有竞争力和有效性.A particle swarm optimization with cooperative search strategy is proposed(PSOCS).Some ideas of PSOCS are inspired by the divisions of roles and cooperations among biological populations.In PSOCS,all particles are divided into two swarms.Different search strategies are used in these two groups,one subgroup has better mining ability,and the other subgroup has better exploration ability.In order to ensure the cooperative search between these two swarms,a strategy of information exchange is adopted in PSOCS.This strategy is embodied in the update equation of the particles.In order to test the performance of PSOCS,numerical experiments are conducted to compare the performance of PSOCS with those of other popular PSO algorithms.Experimental results demonstrate that the proposed algorithm performs competitively and effectively in terms of both solution quality and reliability.

关 键 词：粒子群优化 合作策略 变异策略 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]