Low Carbon Logistics Distribution Route Optimization Based On Hybrid Genetic Algorithm

With the vigorous development of China’s socialist market economy,the proportion of the total benefits of the logistics industry has increased steadily,which is an important pillar to promote the national economic and social development.Half of the benefits of the logistics industry come from material distribution.Material storage,route selection,transportation vehicle scheduling and other factors constitute material distribution.It can be seen that the high energy consuming activity of transporting goods has great destructive power to the environment.The transportation industry mainly depends on oil and other fuels,and the combustion of fossil fuels will release a large amount of carbon dioxide.It is very necessary to develop a low-carbon economy in the transportation industry.In recent years,with the increasing attention of our society to environmental protection,the concept of energy conservation and emission reduction has long been deeply rooted in the hearts of the people.Low energy consumption transportation should be a new trend for the survival of enterprises.This paper studies the distribution path optimization problem with different algorithms with soft time window under low-carbon factors.Firstly,starting with the relevant theories of logistics distribution route,according to the distribution characteristics of low-carbon freight,this paper investigates the influencing factors of running distance on fuel loss and carbon dioxide emission from the optimization mode of logistics distribution route,aiming at reducing the cost of logistics nodes,by considering the cost of loading capacity,distance cost,fixed vehicle price,freight transportation cost,total fuel consumption cost Wait for the goal of minimizing the penalty cost in a specific period of time,introduce the soft time window penalty function,build a low-carbon logistics distribution route mathematical model with soft time window with the goal of minimizing the total cost,use the principle of genetic algorithm to design the algorithm of the model,analyze and compare the advantages and disadvantages of the results obtained by different algorithms,in order to achieve the global optimal solution,Finally,taking the actual distribution situation of H chain supermarket in a certain area as the experimental data,and using MATLAB to realize the program design,the calculation of the established model is completed.The numerical results of the model show that the minimum logistics cost and the best logistics distribution path obtained by the low-carbon vehicle routing method proposed according to the established model and adaptive genetic algorithm not only meet the requirements of consumers,but also save the logistics distribution cost.Genetic simulated annealing algorithm has significant advantages in search,avoiding the problems of local optimization and long iteration time.The results of numerical examples in this paper prove the possibility of quantitative solution of low-carbon route planning,and put forward a solution of great reference value for logistics companies to develop low-carbon operation to meet the personalized requirements of customers.There are 11 figures,7 tables and 68 references.