The Research On An Optimizational Scheduling Of The Operators Checking Returns For Company A

In the modern society of the increasing behavior of returning online retail goods,how to improve the return logistics management to meet the customer’s return needs,ensure the return service level,reduce the operating cost and improve the efficiency of the return logistics are the common problems faced by enterprises.Company A’s online mall is the largest self-operated e-commerce platform in China,providing consumers with high-quality online browsing,trading,after-sales and other full-process one-stop shopping services.In recent years,with the continuous growth of online retail sales,the number of returns is also increasing.In order to protect consumers ’return rights and improve the return experience,Company A continues to optimize the return logistics service level by standardizing the return service process and applying big data technology.Due to the characteristics of uncertainty,slowness and diversity of return orders,Company A still faces the problem of how to dispatch human resources to improve the service level of returned goods logistics and reduce labor costs.This article analyzes the business process,the characteristics of the return order and the current situation of employee scheduling based on the characteristics and status of return checking operation in company A’s reverse warehouse.Through field research,it is found that there are waste of labor costs,unbalanced human efficiency and large number of packages backlog in the personnel scheduling of return processing operations.It is necessary to optimize its personnel scheduling method to improve the efficiency of return processing and reduce waste of labor costs.This article mainly solves the problem of optimizing the scheduling of the return checking personnel of company A.First,qualitatively analyze the factors that affect personnel scheduling,and then combine the actual operating conditions of Company A,and divide the total cost into two parts: the punishment cost that can not meet the service level requirements and the labor cost of wasted employees’ free time.The goal is to minimize the total cost.Using the predicted return volume,compositions of employee skills,work efficiency,service level,etc.of each period as input variables,an integerprogrammed model is established.Finally,taking the company 3C reverse warehouse in North China District of Company A as an example,the actual production data is substituted into the model.A variable neighborhood search algorithm is used to obtain the scheduling plan in the Python program.Then we got the final shift plan by adjusting and improving the initial plan.The results show that the optimized scheme can effectively save labor costs,balance human efficiency and reduce the number of package backlogs,which proves the effectiveness and practicability of the model.This thesis has 9 figures,12 tables,and 47 references.