Analysis And Optimization On Multi-echelon Cold Chain Logistics Network

Recently, as people’s living standards improve, cold chain products arebecoming more and more popular. Eventually, the cold-chain logistics is gainingsteam rapidly. But the cold chain logistics in China started late, there is still a big gapcompared to other developed countries. A series of problems such as the operationmechanism of cold chain logistics in China is not perfect, the logistics facilities andinfrastructure are out of date and the professional level uneven leading to high costand low resource utilization. So establishing a harmonious and well-functioning coldchain logistics network, the use of relevant technology for analysis and optimizationof cold chain logistics network, has some practical significance.This paper is for multi-echelon cold chain logistics network system, whichconsists of a plurality of logistics center multiple producers and multiple clients.According to the actual case of Hubei province, to solve the layout optimizationproblem of the assignment relationships between the nodes and the purchasing cycleof multi-echelon cold chain logistics network based on genetic algorithm.Firstly, this paper summarizes the basic knowledge of cold chain logisticsnetwork, uses self-organization theory to analyze the system, analyses the researchcondition in china and other countries and determines the research mentality and theresearch content on the base of many literatures.Secondly, this paper describes the theoretical knowledge of the logistics centerlocation, combined with the actual situation in Hubei Province. Then we used thelocation model of discrete calculation and analysis to the seven alternatives.Considering the lowest cost, four logistics centers are the best places to establish coldchain logistics centers which could lead to the best economic and social benefits.Finally, after a brief analysis for the concepts, characteristics, basic thoughts andsolving steps of genetic algorithm, the thesis use a mathematical model to optimizenetwork layout, combining GA and the genetic algorithm toolbox of MATLAB toassistant solution.