文献类型：期刊文献

中文题名：基于改进粒子群优化算法的虚拟企业伙伴选择

英文题名：Partner Selection of Virtual Enterprise Based on Improved PSO Algorithm

作者：卜艳萍[1,2];周伟[3];俞金寿[1]

机构：[1]华东理工大学自动化研究所,上海200237;[2]上海交通大学技术学院,上海200231;[3]华东理工大学商学院,上海200237

年份：2008

卷号：26

期号：12

起止页码：62

中文期刊名：系统工程

外文期刊名：Systems Engineering

收录：CSTPCD;;北大核心:【北大核心2004】；CSCD:【CSCD2011_2012】；

语种：中文

中文关键词：粒子群优化算法;适应度值;虚拟企业;伙伴选择

外文关键词：Particle Swarm Optimization Algorithm; Fitness Value; Virtual Enterprise; Partner Selection

摘要：在分析基本粒子群优化算法和建立虚拟企业伙伴选择多目标决策模型的基础上,提出了一种求解供应链联盟伙伴选择的优化问题的改进粒子群算法。在优化过程中,该算法以优良适应值粒子取代部分不良适应值粒子,使算法具有过滤能力,加快了搜索速度,并保证了收敛于全局最优解。实验结果用基本粒子群算法进行了验证和比较,表明该改进粒子群算法具有较好的性能和简单快速准确等特点。
On the basis of analyzing the particle swarm optimization （PSO） algorithm and establishing the multi-objective decision-making model for partner selection, an improved PSO algorithm is presented to the optimize partner selection problems in a supply chain alliance. By replacing the particles with worse fitness values with the feasible particles with better fitness values during the process of optimization, the algorithm has the ability of filtrating, and the searching speed is improved, which can guarantee the global optimal solution being found as well. Moreover, effective performance and experimental results are rapidly obtained through the improved PSO algorithm, which can be confirmed by the method of basic PSO algorithm.