基于富网络属性路网模型配送问题研究及仿真

Research of Multi-depots Logistics Distribution Problem Based on Rich Network Road Model

为解决多仓库对多客户点进行配送以及在配送过程中车辆调度决策者面对道路突发状况的应急问题,采用组合优化算法对配送提供最短路径和最短时间两种决策模式进行研究.首先建立GIS富网络模型,包含道路等级权值,同时根据不同等级建立不同行车速度,求得相应的距离最短和时间最短OD矩阵;其次借鉴系统生物学中进化树分类的思想,对目标节点动态回溯分类,有效降低客户点数目,实现多仓库货存量协调优化;再次,建立配送模型,将非线性问题转化为线性问题,进而,采用线性规划计算得到配送方案.最后,结合杭州市卷烟配送实例验证了算法的有效性.

The multi-depots logistics distribution problem is a particular combination of transportation and vehicle routing problems, in which items that have to be loaded into different customers within vehicles, and then delivered with minimum cost. In this paper, A GIS rich network model is built firstly and the weights between the roads are acquired by GIS software; Next, the idea of the evolutionary tree classification is used to solve the nonlinear cost variables in the distribution model. Extensive computational results show that the proposed algorithm are capable of solving to optimality for a large number of small-size instances, and consistently outperform previous algorithms from the literature on large-size and real-world instances.