Research On Picking Operation Optimization In A E-commerce Company's Distribution Center

With the continuous development of e-commerce,the distribution center of electric commercial enterprise receives more and more customer orders which are small volumes of different articles.And the demand of the distribution center operation performance is required higher and higher.As a core distribution center functions,order picking significantly affects the efficiency of distribution center operations.Therefore,the study of order picking has important practical significance.This thesis mainly discusses the order batching problem and the picking route optimization problem in the distribution center.On the basis of summarizing and analyzing the scholars' previous researches,in this thesis an order batching model and a picking route optimization model are formulated.The models minimize the total travel distance over all batches and tours.Then genetic algorithm is proposed to solve the order batching problem and the picking route optimization problem.In order to analyze the order batching problem,the author used the same data of customer orders and compared the order batching approach proposed by this thesis with the order batching approach used in the distribution now.It is proved that the travel distance significantly reduced by using the genetic algorithm to solve the order batching problem.In order to analyze the picking route optimization problem,the author compared the result of optimized route which used genetic algorithm with the S-shape route used by the distribution center.It is proved that the travel distance significantly reduced by using the genetic algorithm to solve the picking route optimization problem.This thesis uses Matlab genetic algorithm for solving the two models which are order batching model and picking route optimization model.