Order Picking Optimization Considering Splitting Strategy In Distribution Center

In recent years,e-commerce has developed rapidly,and it has been favored by more and more consumers for its advantages,such as the convenience and product diversity.In the ecommerce environment,the daily order quantity for online shopping can reach hundreds of thousands,and customer orders are characterized by small batches,multiple varieties,short response times.These features significantly increase the difficulty of order picking in the distribution center.On the other hand,order picking is the most labor-intensive and costintensive activity in warehouse operations,and its cost accounts for more than 55%of the total warehouse’s operating costs.The efficiency of order picking directly affects the distribution center’s operating cost and service quality.Therefore,in order to ensure that products are delivered to customers on time,an efficient and accurate order picking strategy is necessary.The order splitting strategy reduces the order processing time by increasing the load rate of the picking equipment and reducing the picker’s travelling distance,thereby reducing the total tardiness of the order and improving customer satisfaction.In summary,it is of great theoretical and practical significance to study the order picking optimization problem of distribution centers considering splitting strategies.Based on the existing literature research,this paper considers the impact of two order splitting strategies,namely due time similarity splitting and location similarity splitting,on order picking efficiency,according to the characteristics of customer orders in e-commerce environment.With the goal of minimizing the orders’ total tardiness,this paper constructs the distribution center order picking optimization model and applies the model to the actual.The main research work of this paper is as follows:(1)Research on order picking optimization considering due time similarity splitting.Firstly,according to the characteristics of customer orders,the due time similarity splitting strategy is proposed in order to improve the efficiency of order picking.Based on the consideration of the capacity limit of the picking equipment,an order picking optimization model considering due time similarity splitting is constructed.Secondly,according to the established model,this paper designs the order batch method considering the due time similarity splitting strategy and the knowledge-guided fruit fly optimization algorithm to solve the model.Finally,a numerical example shows that when considering the due time similarity splitting strategy,the total delay time is significantly smaller than that without considering the order splitting.And it is found the performance of the knowledge-guided fruit fly optimization algorithm is better than the ESD algorithm.(2)Research on order picking optimization considering location similarity splitting.Firstly,on the basis of considering the order picking optimization problem of the due time similarity splitting,the impact of location similarity splitting on order picking efficiency is studied.Aiming at this problem,an order picking optimization model considering location similarity splitting is constructed.Secondly,the model was solved using the order batch method considering the location similarity splitting strategy and the knowledge-guided fruit fly optimization algorithm.Finally,a numerical example analysis shows that the position splitting strategy reduces the total travelling distance by allocating sub-orders with similar location to the same picker,thereby reducing the total delay time.The feasibility of order picking optimization model considering location similarity splitting and the effectiveness of knowledge-guided fruit fly optimization algorithm are verified.(3)Potential Application Research:Take Company A as an example.Firstly,the background and the order picking situation of company A were introduced.Secondly,based on the actual data of the company’s orders,the order picking model based on due time similarity splitting and location similarity splitting is solved by the order batch method considering the splitting strategy and the knowledge-guided fruit fly optimization algorithm.The optimal order batching,batch assignment and sequencing schemes are obtained.Finally,the optimal order picking scheme provides corresponding theoretical guidance for the actual operation of Company A.This paper studies the order picking optimization problem of the distribution center considering the due time similarity splitting and location similarity splitting.Compared with the existing research,this research can better meet the requirements of the actual distribution center to improve the order picking efficiency,and thus can provide a decision reference for the actual order picking.