面向电子商务的协同配送路线优化研究

电子商务环境下的协同配送具有客户位置分散、订单多、批量小和重复线路多的特点,传统的线路优化方法都在不同程度上遇到各种问题,难以有效。因此,针对电子商务环境下的配送特殊性,采用改进两阶段算法进行求解:第一阶段用K-means聚类法将客户群分成若干区域,在每个区域又用扫描算法分解成若干符合约束条件的小规模子集;第二个阶段对各个分组内的客户点,就是一个个单独的TSP模型的线路优化问题,采用改进遗传算法进行优化求解。最后,结合具体实例,实验证明该改进算法的有效性。

Research on cooperating distribution routing of optimization for electronic commerce

The cooperating distribution under electronic commerce environment has the character of dispersive customer positions, large order forms,little batches and many repeated routes.The traditional optimizing route methods meet with diversified problems in different extents and are difficult to play their roles.Therefore,according to the particularity of logistic distribution under electronic commerce environment,the improved two-phase algorithm needs to be adopted to get solutions.Namely,the customer group can be divided into several regions using K-means clustering method in first phase.And in every region it can be decomposed into small scale subsets according with some restraint conditions using Scan Algorithm.In second phase,get the solutions of the customer point in every group using the Improved Genetic Algorithm.In fact it is route optimization problems of several single TSP model.In the end,the test proves the validity of this improved algorithm combining with examples.