摘要
针对敏捷供应链组建过程中伙伴选择的特点,提出了一种基于多种群协同进化的改进量子粒子群算法.在对该算法的设计中,首先将整个量子粒子种群分解为多个子种群,然后使各个子种群进行独立的演化,并通过周期性的共享搜索信息获得对自身信息的更新,最后通过具体的算例对该算法进行了仿真验证.研究结果表明,在算法的收敛性、最优性等方面,基于多量子粒子种群协同进化算法均达到了良好的效果.
According to the characteristic of partner selection in the process of buildup of agile supply chains, a new quantum particle swarm optimizer, called the cooperative evolutionary QPSO with multi-populations（MC-PSO）, is presented based on the analysis of the standard QPSO. The whole quantum particle swarm group is divided into several sub-groups. Every subgroup evolved independently and updated sharing information periodically. Finally we use a practical analyses to confirm the performance of the method. The results show that MC- QPSO is effective in solving the problem.
出处
《陕西科技大学学报（自然科学版）》
2009年第3期161-164,173,共5页
Journal of Shaanxi University of Science & Technology
基金
国家自然科学基金项目(项目编号:50605048)
关键词
量子粒子群算法
多种群
协同进化
敏捷供应链
伙伴选择
quantum particle swarm optimization （QPSO）
multi-populations
cooperative evolutionary
agile supply chains
partner selection
