Research On Distribution Routing Optimization Of Low-carbon Cold Chain Logistics Based On Prospect Theory

With the gradual increase in China’s consumption level,the fresh food e-commerce market has seen unprecedented development,with strong demand for cold chain logistics and strong development momentum.In 2021,the General Office of the State Council issued the "14th Five-Year Plan" for the development of cold chain logistics,which made comprehensive arrangements for the development of cold chain logistics during the 14 th Five-Year Plan period,clearly proposing that a modern cold chain logistics system should be fully established by 2035,giving full play to the important role of cold chain Logistics plays an important role in promoting consumption and improving people’s livelihood.However,the cold chain logistics industry still suffers from high transportation costs,low quality of transportation services and high carbon emissions during transportation.How to keep pace with the policy and firmly promote the high quality development of the cold chain logistics industry while implementing the goal of "double carbon" policy is an urgent issue for the cold chain logistics industry at present.Therefore,this paper considers the economic benefits of the cold chain logistics industry,further enhances the quality of service,while integrating the green concept into the cold chain transport industry,and builds a low carbon cold chain logistics distribution path with low cost,high quality service and green environment protection in a three-pronged approach.This paper focuses on cold chain products as the research object,and the main research content is divided into four parts.Firstly,by reviewing relevant literature,it summarizes the research on the low-carbon vehicle routing problem model,solution algorithms,and prospect theory that consider customer satisfaction.The multi-objective path optimisation model with the lowest cost,highest customer satisfaction and lowest carbon emission is established,in which the cost includes vehicle fixed cost,transportation cost,cargo damage cost,energy consumption cost and penalty cost;Again,by comparing and analysing various optimisation algorithms,to solve the above model,the non-dominated ranking genetic algorithm(NSGA-Ⅱ)is chosen.Regarding the algorithm design,to address the shortcomings of NSGA-Ⅱ in the slow search speed when solving on a large scale,the grey wolf optimization algorithm(GWO)with strong convergence function was introduced,and the "social hierarchy stratification" and "prey encirclement" steps in the grey wolf algorithm were replaced by the "selection" steps in NSGA-Ⅱ."The NSGA-GWO algorithm is designed to improve the computational speed and solution accuracy of the model.Finally,a simulation experiment is conducted using the Solomon standard data set to obtain the distribution solution with the lowest cost,highest customer satisfaction and lowest carbon emission,which verifies the practical feasibility of the model.This paper takes into account the cost,customer satisfaction and carbon emissions of cold chain logistics enterprises,and constructs a low-carbon cold chain logistics distribution path optimization model based on prospect theory,which provides some theoretical basis for cold chain logistics enterprises to choose transportation solutions rationally,and hopefully provides reference and reference to improve the economic efficiency and competitiveness of enterprises.