Optimization Model On Two-echelon Logistics Distribution Problem Of Large Scale Online Supermarket

Nowadays,the large scale online supermarket has become the new trend of e-commerce.This new selling style has gradually been favored by consumers and become one of the mainstream goods retail.However,the high logistics costs caused by unreasonable distribution strategy,has become a major factor hindering the development of large scale online supermarket.The logistics delivery problem of large scale online supermarket is essentially a two-echelon Capacitated Vehicle Routing Problem with time windows.The research on two-echelon Vehicle Routing Problem with the applied background of large scale online supermarket,can not only help companies reduce logistics costs,improve order fulfillment efficiency,and achieve the rational allocation of resources,but more importantly also can help companies serve their customers better and improve the consumers’ satisfaction level.Firstly,through the analysis of actual situation of large scale online supermarket’s logistics delivery,and the research of basic theories on two-echelon Capacitated Vehicle Routing Problem with time windows,a mixed integer programming model is built for Two-Echelon Vehicle Routing Problem with time window,which has the constraints of order delivery time,vehicle capacity,vehicle travelling distance and workload balance of satellite stations.Then,according to the characteristics of the orders of large scale online supermarket,by fuzzy clustering,we pre-group the costumers.Under this basis,we propose a customer grouping algorithm for 2E-VRP of large scale online supermarket,develop a algorithm for solving Two-Echelon Vehicle Routing Problem of large scale online supermarket base on C-W saving algorithm,and a customer grouping improvement algorithm based on current results of optimization.Finally,we design a solving system for 2E-VRP of large scale online supermarket including three modules,which are online supermarket customer grouping algorithm module,scheme generation module of 2E-VRP,and customer grouping improvement algorithm module.By adding random satellites to fit our background,a case transformed from the Solomon case is solved,which proves the effectiveness of the solution algorithm.This research provides a new method for two-echelon logistics distribution optimization decision of large scale online supermarket,provides a new tool for computer to generate logistics distribution scheme online and intelligently,promotes cross and fusion of artificial intelligence and the related subject of operations research,improves scientificalness,practicality and universality of theory of orders sorting and logistics distribution,develops the e-commerce mode of large scale online supermarket,riches and perfects e-commerce logistics management theory.In practice,the theory can be used to guide actual activities of distribution center order picking personnel and vehicle scheduling personnel of large scale online supermarket or other B2 C e-commerce,helps e-commerce enterprises to upgrade the efficiency and customer service levels,so as to enhance its competitive advantage.