Joint Optimization Of Location Assignment And Picking Route For Two-block Warehouse Based On Tabu Search Algorithm

With the rapid development of global trade and continuous expansion of the market,logistics,as the significant supports for the national economy,combines each part of social production together,which has become a crucial means for enterprises to improve their competitiveness.Besides,the improvement of logistics system also further promotes the development of e-commerce.In recent years,e-commerce enterprises have gradually increased their market share.However,with the products showing the characteristics of short cycle,large changes in market demand and multiple types,the current operation mode of "location assignment first,then pick" becomes no longer applicable.Therefore,some researchers have paid attention to joint optimization of location assignment and picking path,which has important practical significance to reduce cost and improve operation efficiency.This thesis particularly considers the complexity and randomness of the received orders in realistic warehousing and distribution centers.With considering the capacity of picking truck(i.e.,whether the received order can be completed by one picking operation),two mathematical models of one truck for one order and multiple trucks for one order are proposed separately for the two-block warehouse,in which both the storage cost and picking operation cost are taken as the objective function.In order to solve the proposed models,a tabu search algorithm is developed.And,a series of numerical experiments are carried out to verify the effectiveness and rationality of the proposed models and algorithm.The contributions of this thesis are threefold.(1)This paper first analyzes the basic functions and operational process of the warehousing and distribution centers,and summarizes the basic strategies and principles of goods storage.Then,this paper explores the relevant theory of picking operation,and determines the picking operation process.Furthermore,by comparing and analyzing different strategies of picking route,the suitable optimal route strategy is selected.Considering the diversity of customer demands,sometimes,there are a large number of goods to be picked up in the orders received by the warehousing and distribution centers.In this case,it usually takes many times of picking trucks to complete the picking task.Thus,two mathematical models of one truck for one order and multiple trucks for one order are respectively formulated.(2)Based on the two-block warehouse,we propose a two-stage stochastic programming model for the joint optimization of location assignment and picking route.The first stage of the model aims to minimize the storage cost,and the second stage aims to minimize the picking operation cost.In order to solve the proposed models,a tabu search algorithm is developed.Furthermore,a series of numerical experiments are carried out to compare and analyze the optimization results of the model of one truck for one order under three conditions(i.e.,optimization of the picking route only,optimization of the location assignment and the picking route separately,and joint optimization of the location assignment and picking path).(3)Considering the limited capacity of picking trucks,it usually needs several picking trucks to complete all picking tasks.Based on the model of one truck for one order,the model of multiple trucks for one order is proposed for joint optimizing location assignment and picking route by adding some basic assumptions.Similarly,a tabu search algorithm is developed to solve the proposed model.And several numerical experiments are designed with further considering some new parameters,such as the maximum capacity of the picking truck and the weight of the goods required for the picking order.What's more,we also compare and analyze the different changes of the cost for the solutions generated by the models of one truck for one order and multiple trucks for one order under the considered three conditions(i.e.,optimizing the picking route only,optimizing the location assignment and the picking route separately,and optimizing the location assignment and picking route cooperatively).