Research On Multi-objective Path Planning Problem Of Cold Chain Logistics With Carbon Emission And Fuzzy Time Windows

With the acceleration of life pace and constant improvements of people’s quality of life,the demand for fresh agricultural products is ever increasing,which,therefore,becomes an important promotion of cold chain logistics.Meanwhile,people are paying more and more attention to the quality and freshness of fresh agricultural products.Based on the timeliness of fresh agricultural products,time windows have become an important factor of distribution path planning for cold chain logistics enterprises so as to meet customers’ time of delivery.Besides,green logistics is emerging,and cold chain logistics distributions with high energy consumption and carbon emission go against the national energy-saving and emission reduction policy under the background of global warming.Therefore,in order to achieve long-term development,companies have to change the distribution mode to improve economic efficiency.At the same time,the low carbon emission of distribution vehicles has also become an important factor of the enterprises ’ sustainable development.Therefore,studies on cold chain logistics distribution paths addressing carbon emission would contribute to the sustainable development of both companies and the nation.This thesis focuses on the optimization model of cold chain logistics vehicle distribution path.First,domestic and foreign researches on cold chain logistics and vehicle routing problems are reviewed with focus on current research literature of carbon emissions and multi-objective optimization.Contributions and shortcomings of the reviewed literature are summarized,motivating this thesis’ study.Second,in terms of the optimization model,this thesis analyzes related theories on vehicle path and its optimization problem with time windows and carbon emissions,and the feasibility of the proposed model for application in enterprises is confirmed.In terms of model solution,the precise algorithm,heuristic algorithm,and intelligent optimization algorithm are elaborated and discussed,and the intelligent algorithm demonstrating thebest optimization ability is finally employed.Furthermore,a multi-objective cold chain logistics route optimization model with carbon emission was established solving the cold chain logistics route optimization problem.The model aims at the lowest total distribution cost and carbon emissions as well as the highest customer satisfaction,while including fuzzy time window under actual distribution situations.By descaling quantization and determining the weight of each objective function,three objective functions are integrated into one objective function,minimizing the total objective to achieve the joint optimization of the three objectives.Finally,this thesis employed an improved genetic algorithm to solve the above problem.The adaptive operator and the catastrophe operator are integrated into a standard genetic algorithm coded in MATLAB software with C language.Based on the cold chain logistics distribution of Y enterprise in Shanghai,China,the distribution route optimization problem was calibrated with real data.An optimal solution was reached,and the results were analyzed.Results show that routes calculated with the proposed model are more economic and environmental friendly,demonstrating better optimization ability and more reasonable and effective than those of standard genetic algorithm and auto adaptive catastrophe genetic algorithm.This thesis proposed a multi-objective path planning model of cold chain logistics based on carbon emission of distribution vehicles,which provides a foundation for the government implementing carbon emission reduction policies in cold chain logistics enterprises.Cold chain logistics enterprises would also benefit in terms of standardized operation and long-term development.The adaptive catastrophe genetic algorithm developed in this research would shed light on the solution of cold chain logistics distribution model.