A new cluster-structured Particle Swarm Optimization (PSO) with interaction and diversity of parameters is proposed in this letter. After a swarm of PSO is divided into some sub-swarms (clusters), interactions between sub-swarms and diversity of PSO parameters are added so as to improve the search ability of PSO in the proposed cluster-structured PSO. The feasibility and the advantage of the proposed cluster-structured PSO are demonstrated through numerical simulations using two typical optimization test problems.