基于城市配送平台的订单与车辆匹配优化策略

Order and Vehicle Matching Optimization Problem Based on Urban Distribution Platform

对于货物配送过程中零担订单与配送车辆的匹配问题,由于传统的人工匹配模式会导致较高的运输成本和空载率。针对此问题,根据实际业务情况,将订单体积与重量作为约束条件,以平台利润最大化为优化目标建立0-1整数规划模型。根据平台实际业务设计出GAPVR (Genetic Algorithm based on Price-Volume Ratio)算法,并将该算法与CPLEX和平台目前的业务操作采用的FCFS(First Come First Service)算法进行对比。通过在不同订单量下进行数值模拟分析,结果表明在大规模订单量下,设计的GAPVR算法可以有效节约17.24%的运输成本,并在此前提下,可以进一步将空载率降至平均4.73%,比平台当前FCFS算法的空载率降低50%,证明了模型的有效性,对平台的实际运营具有一定的指导意义。

The matching problem between the LTL order and the delivery vehicle during the goods distribution process has been proposed.The traditional manual matching mode has led to higher transportation cost and non-load rate.From this perspective,the 0-1 integer programming model based on the actual business situation has been established,taking the order volume and weight into consideration with an aim to maximize the platform profit.Besides,a GAPVR algorithm has been designed according to the actual business of the platform.Compare this mothed with CPLEX and the FCFS algorithm which comes from the current business operations of the platform.Through numerical simulation analysis under different order quantities,the results show that under the large order quantity,the designed GAPVR algorithm can effectively save 17.24% of transportation cost,and under this premise,the non-load rate can be further reduced to an average of 4.73%,which is 50% lower than the current FCFS algorithm’s non-load rate.It proves the validity of the model and has certain guiding significance for the actual operation of the platform.