随着电子商务的发展，电子商务企业服务器集群负载均衡问题越来越严重，为了解决粒子群算法在求解电子商务服务器集群负载均衡问题上存在的不足，提出一种改进的文化粒子群算法的服务器集群负载均衡策略。首先利用粒子群算法的主群体空间和文化算法的知识空间形成“双演化双促进”机制，提高算法全局搜索能力和运行效率；然后引入遗传算法进化机制对知识空间演化操作进行改进，最后将该算法应用于电子商务服务器集群负载均衡问题求解。经过仿真验证，改进文化粒子群算法，提高服务器集群系统资源利用率，负载更加均衡。%In order to solve problems of particle swarm optimization algorithm in solving the load balancing for large E-commerce server cluster, this paper proposes a large E-commerce load balance method based on improved cultural particle swarm optimization algorithm. Firstly,a main population space of particle swarm algorithm and spatial knowledge of cultural algorithm form the"dual evolution and dual promotion" mechanism to improve global search capability and ef-ficiency;and the evolutionary mechanism of genetic algorithm is introduced to improve the knowledge space and avoid self limiting of culture algorithm,and finally,the algorithm is applied to the solution of load balancing problem for large E-commerce server cluster. The simulation results show that the proposed algorithm has improved resource utilization rate of large E-commerce server cluster system and that the load is more balanced.
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