An Improved Algorithm for Multi-Swarm Particle Swarm Optimization Based on Clustering Algorithm

This paper studies the effects of logical random grouping and physical location grouping on the performance of multi-population particle swarm optimization (MSPSO) algorithm and realizes the dynamic grouping of multi-swarm particle optimization algorithms by introducing clustering algorithm. And the effects of K-Means algorithm, K-Medoids algorithm and DBSCAN algorithm on MSPSO are compared.