Research On Multi-objective Optimization Model Of Two-Echelon Vehicle Routing Problem

In recent years,the new retail industry of the Internet of Things has been changing with each passing day,and smart logistics has developed rapidly.The people's demand for time-efficiency and higher service levels of express delivery has made logistics companies no longer only choose low-cost and high-efficiency distribution routes.Urban green sustainable development is taken into consideration.The problem of logistics distribution vehicle path planning has entered a new critical period.Two-echelon logistics distribution is the most basic and most common mode in the current urban logistics distribution system.Therefore,the two-echelon logistics distribution system in the new environment In-depth research on the problem of vehicle routing can not only meet the service demands of consumers,but also have important practical significance for improving urban traffic conditions and promoting energy saving and emission reduction.This article mainly focuses on economic benefits,environmental pollution and noise nuisance.Research the two-echelon vehicle routing problem based on customer classification and time window restriction,establish a mixed integer nonlinear programming model with the goal of minimizing economic costs,environmental impact and social interference,based on improved C-W saving algorithm and large-scale neighborhood search algorithm solve and test through customer examples of different distribution types.The first chapter mainly introduces the background and significance of the twoechelon vehicle routing problem,analyzes and summarizes the domestic and foreign research status and development process of the two-echelon vehicle routing problem,the two-echelon vehicle routing multi-objective optimization model and its solution algorithm.The second chapter provides an overview of the two-echelon vehicle routing problem and the theory of multi-objective optimization.First,the relevant definition and classification of the two-echelon vehicle routing problem are explained from the basic elements and components of the two-echelon logistics distribution;Secondly,based on classification,researched and sorted out the two-echelon vehicle routing optimization model considering capacity constraints,with time windows and with locker facilities;Then,analyze the solution ideas of the two-level vehicle routing problem from the three aspects of customer allocation,”depot-satellite” and ”satellite-customer”,that is,the application of clustering algorithm,precise algorithm and heuristic algorithm;Finally,a summary of the theory and methods of multi-objective programming.The third chapter studies the two-echelon vehicle routing problem considering customer classification and time window restrictions.First,for the two-echelon urban cargo transportation process,the customer classification based on regional division,the satellite setting with storage function and the processing of the customer's fuzzy time window are proposed;Secondly,considering various effects such as economic benefits,environmental pollution and noise nuisance,establish a mixed integer nonlinear programming model with the goal of minimizing economic costs,environmental impact and social interference;Finally,based on the K-means clustering algorithm and improved C-W saving algorithm design large-scale neighborhood search algorithm.The fourth chapter is mainly for case test and case analysis.Through the Solomon case of different distribution types,the case test is carried out on the effectiveness of customer classification and the number of different satellites.On this basis,the single-target model and the multi-target model are solved.Analysis and verification of the effectiveness of the model and solution algorithm established in this paper.