【作者】 周伟； 卜艳萍；

【Author】 ZHOU Wei 1 BU Yan-ping 2 1. School of Business, East China University of Science and Technology, Shanghai, 2002372. School of Technology, Shanghai Jiaotong University, Shanghai, 201101

【机构】 华东理工大学商学院； 上海交通大学技术学院；

【摘要】 基于文化算法和传统的微粒群优化(PSO)算法,本文提出了一种文化微粒群优化(CPSO)算法。在改进的算法中,采用双层进化机制,并重新定义了文化算法的种群空间和信念空间。应用该算法求解虚拟企业伙伴选择问题。在虚拟企业中,由候选伙伴的合作来完成任务。优化目标是使总的开销最小和任务完成时间最短。最后,通过实例仿真,对该算法性能进行比较分析和评价,结果表明了该算法的有效性和可行性。更多还原

【Abstract】 Based on cultural algorithm and classical particle swarm optimization (PSO) algorithm, a cultural particle swarm optimization (CPSO) algorithm is proposed. In the improved algorithm, double evolutionary mechanisms are used. The population space and the belief space of cultural algorithm are redesigned. The proposed model was used to solve the partner selection problem of virtual enterprise. In a virtual enterprise, the whole task can be accomplished by the cooperation among those candidate partners. The optimal objective is to minimize the total cost and completing time. Finally, the performance of the algorithm is evaluated by simulations. Results demonstrate the feasibility and efficiency of the proposed algorithm.更多还原