Joint Optimization Of Distribution Scheduling And Route Planning Of Food Cold Chain Under Demand Surge

Recently,Chinese economy is developing rapidly.The food cold chain logistics is also rapidly developed to meet the growing demand of consumers.The government have introduced various favorable policies to further promote the development of cold chain logistics.Consumers pay more and more attention to the delivery process of fresh food while paying attention to the price.This dissertation researched the problem of joint optimization of distribution scheduling and route planning of food cold chain under demand surge.Firstly,the background of the problem was considered.On this basis,the domestic and foreign literatures related to the research in the dissertation were searched and summarized.This dissertation researched and summarized from the four aspects of demand surge,distribution scheduling,distribution route planning and joint optimization model and algorithm respectively.The dissertation analyzed the distribution schedule and route of the food cold chain and expounded the connotation and characteristics of the food cold chain distribution under demand surge.The dissertation analyzed the influenced factors of the food cold chain distribution schedule and path,and then analyzed the goal and direction of optimization.Secondly,in order to solve the problem of high cost and long time of food cold chain distribution under demand surge in the case,a mathematical model was established.This dissertation divided two cases:the offline and online orders,with the minimum time and minimum cost as the objective function for modeling.In the case of offline orders,an algorithm was designed to solve the problem.First,all customer orders were clustering analyzed by K-means++algorithm,and then the order distribution scheduling(order batching)and path joint optimization was carried out in each region using the genetic algorithm.In the case that the online order,an algorithm is designed to solve the problem too.First,the customers are classified into different regions by using historical data,and order batch and insertion rules are formulated in the regions.Then,the distribution scheduling(order batching)and path were optimized by using genetic algorithm.Finally,this dissertation taked the e-commerce platform of X company as the case background and collected the actual operation data of the enterprise to solve the model.Then drew conclusions by using MATLAB to program and run the program to verify the effectiveness of the model and algorithm.The results of the present segmented optimization scheme and the joint optimization were compared in terms of total delivery time,total delivery cost and total delivery mileage.And the results of two cases of offline and online orders were compared too.Through the analysis of the results,we can get the inspiration for the enterprise's operation and management decisions,and also put forward reasonable suggestions for customers.There are 27 figures,15 tables and 97 references in this dissertation.