E-commerce Orders And Local O2O Orders Jointly Optimize The Distribution Path

With the rapid rise of E-Commerce,the logistics industry has entered a new peak.At present,logistics packages generated by online shopping account for 60% of China's logistics volume.How to deliver the package to consumers more efficiently and conveniently is an important link at the end of logistics distribution.At present,the package delivery mode in this link is mainly divided into two types: one is that the Courier delivers the package directly from the network to the customer's home;the other is the intra-city O2O package delivery caused by offline Internet penetration.These two categories are typical models of the last kilometer of logistics in China.The research of this paper is to provide intelligent distribution scheme for the last kilometer of logistics through data analysis,and to improve distribution efficiency and reduce distribution cost through global optimization.The combination of E-Commerce order distribution and intra-city O2O order distribution can bring greater economic benefits.This paper analyzes the problems and constraints in the process of combining the two,builds a distribution model,optimizes the distribution path,and excavates the optimization algorithm,so as to maximize the economic benefits.The main contents are as follows:1.At the beginning,the paper briefly introduces the related theoretical research on CVRP and VRPPDTW of two kinds of vehicle path optimization models,analyzes the research status of "last kilometer" extreme speed distribution,and then summarizes the vehicle path problem algorithm,providing theoretical support for the subsequent path planning algorithm design.According to the characteristics of the "last kilometer" distribution problem,this paper constructs the distribution models of E-Commerce orders and intra-city O2O orders respectively with the goal of minimizing the distribution distance.2.Based on the path planning of O2O package in the same city,a path planning model with time window and simultaneous delivery vehicle is established.Then,the distribution area is divided by K-Means++ clustering algorithm,then the minimum cost and maximum flow algorithm(MCMF)is used to build the network,and thegenerated distribution path segment is solved,and the obtained results are combined with dynamic programming to get the delivery plan of O2O package in the same city.3.Based on the path planning of E-Commerce package,a vehicle path planning model considering the maximum load was established.To minimize the distribution distance as the objective function,the initial feasible solution is generated by CW method,and then the solution is processed by Tabu Search algorithm to obtain the distribution scheme of E-Commerce orders.4.Based on the path planning of the joint delivery of O2O packages and E-Commerce packages in the same city,the 0/1 backpack combination algorithm was used in the combination of path segments,and then the waiting time of the delivery of O2O packages was optimized.Finally,in order to verify the effectiveness and practicability of the algorithm,the results of joint distribution calculated by the traditional heuristic algorithm are compared.