基于聚类的物流节点模型及其自适应蚁群算法

A Clustering Model and its Adaptive Ant Colony Algorithm in Logistics Service Nodes layout Optimization

综合考虑物流服务节点区域的空间属性和成本约束,基于物流服务节点波及范围,分析备选服务节点选择过程及其运行成本特征,构建了物流服务节点布局优化模型。将物流服务节点选择映射为一个聚类过程,提出解决物流服务节点选择问题的自适应蚁群聚类算法。以物流系统总成本最低为聚类准则,描述了物流节点布局模型的求解过程,并对服务节点布局参数进行仿真实验,验证模型及算法的鲁棒性和选择效率。

Based on synthetic consideration of space feathers and cost constraint in logistics service node layouts,this paper established a clustering model of nodes selection take into account of its service radius.And though mapping the nodes selection as a clustering process,this paper further proposed an adaptive ant colony clustering algorithm,and solving the layout optimization problem with norms as lowest total system costs.A simulation experiment is done to show that the adaptive ant colony algorithm can deal with the logistics nodes layouts problem with more efficiency and robustness.