Research On The Optimization Order Picking Operation In New Retail

With the rapid development of e-commerce,the upgrading of consumer attitudes and the appearance of "new retail" mode make the offline retail industry's ecology change constantly.In recent years,the growth of total retail sales of social consumer goods in China entered a new normal and growth began to stabilize.In the past three years,traditional online retailers suffered from the "trend" of closing stores due to the influence of online suppliers.However,as far as the overall FMCG market is concerned,even under the influence of online sales,offline sales still account for 74%(Source: Nielsen Market Research,2017),so offline is still the main position of FMCG.If the traditional retail enterprises can be transformed in time,there will still be very good prospects for development.New retail is based on online technology,offline traffic and resources as the basis,the main link to the logistics for the target consumer to provide a scene-based consumption of a model,the core is to enhance the user experience.Among the new retail business,online businesses account for over 60%,some mature stores have reached 70% and there will be more in the future.Online within three kilometers to provide the fastest half-hour door-to-door service,which for the warehouse,it requires the order must be ten minutes(including the order response,picking preparation,picking,packing list,packing time,etc.)The order picking operation is the most complex warehouse,the most labor intensive and the highest proportion of the cost of the link.In the new retail requirements of high efficiency,the order picking operations research is necessary.In order to solve the problem of order picking job optimization under new retail scenario,the factors such as the new retail picking aging,picking strategy and the partitioning workload balancing are considered to minimize the sum of standard deviation of order picking completion time and partition picking completion time of each batch of orders As the objective function,construct the order picking model under the new retail scenario.The non-dominated ranking genetic algorithm with elitist strategy(NSGA-?)was used to solve the model.Finally,in the case study,we construct an order picking model that does not consider the partition workload balance,and compare the two model results to verify that the picking model considering the partition workload balance is more effective.The analysis results show that the research results of this paper can improve the efficiency of order picking operation in new retail and satisfy the order picking aging requirements of new retail.Moreover,the order picking strategy proposed according to the aging requirements of new retailing can provide certain optimization ideas for the picking operation of new retail orders.The research on the thesis has certain practical significance.