摘要
提出了一种解决多物流配送中心选址问题的蚁群算法模型,该模型将物流配送中心选址映射成一个聚类过程,利用蚁群系统中蚂蚁通过信息素寻找最优路径的机制,以物流配送的总成本最低为聚类准则,结合蚂蚁将物体聚堆的行为模式来定义蚂蚁的转移概率、禁忌列表和信息素更新方式,实现基于蚁群优化的物流配送中心选址算法.对多配送中心选址进行了仿真实验,实验结果表明本算法能获得与实际情况相符的配送中心最优解,且适合多种不同的配送中心模型和大规模的配送中心选址,具有较强的灵活性.
A new model is proposed for logistics distribution center allocation based on the ant colony optimization in this paper. Inspired by the ability of real ants to find the shortest path through the laying down of pheromone and to cluster corpse in the nest, we mapped the problem of the logistics distribution center allocation to the process of clustering objects with emphasis on the lowest logistics costs and appropriately designed the transition probability, the tabu list as well as the way pheromone was updated. A detailed logistics distribution center allocation algorithm based on the ant colony optimization is experimented and the experimental results show that the new algorithm can acquire the optimal solution that is accord with the practice, Moreover, the new algorithm has much more flexibility which adapts to many kinds of logistic distribution model and large-scale logistic distribution center allocation.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2006年第4期120-124,共5页
Systems Engineering-Theory & Practice
基金
广东省社会科学"十五"规划课题(03104L04):"‘珠三角地区’物流园区运作模式研究"基金资助
关键词
物流
配送中心选址
蚁群算法
智能优化
logistics
distribution center allocation
ant colony algorithm
intelligent optimization