提出一种融合微粒群的多种群协同免疫优势克隆选择算法(PMCICA).该算法将生态学中的协同进化思想引入人工免疫算法中,各子种群内部通过免疫优势克隆选择操作加快了种群收敛速度;所有子种群共享经过改进微粒群优化的高层优良库,实现了整个种群信息共享与协同进化.针对旅行商问题(TSP)的多个实验结果表明,该算法在收敛速度与最优解等方面均取得了较好的效果. This paper proposes a multi-population coordinated immune predominance clonal selection algorithm (PMCICA) based on particle swarm optimization, which introduces the idea of ​​co-evolution in ecology into artificial immune algorithm and accelerates population convergence by immune dominant clonal selection within each subpopulation ; All sub-populations share the high-level good library with improved particle swarm optimization to achieve the whole population information sharing and co-evolution. A series of experimental results for TSP show that the proposed algorithm is superior in terms of convergence rate and optimal solution Have achieved good results.