具有合作策略的粒子群优化算法

Particle Swarm Optimizer with Cooperative Search Strategy

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.