Research On Vehicle Routing Optimization Of Fresh Products Of Mixed Fleet With Electric Vehicles And Fuel Vehicles

In the context of the national development strategy of "carbon peak" and "carbon neutrality",it is a trend that the traditional fuel vehicles with high emissions and high energy consumption are gradually being replaced.It can be foreseen that electric logistics vehicles will usher in a broad development prospect.However,due to factors such as inadequate facilities and limited charging technology,electric logistics vehicles have not yet been fully popularized.The hybrid distribution of electric and fuel vehicles is more suitable for the actual operation of logistics enterprises at this stage.Under the situation of continuous and multi-point distribution of COVID-19,fresh food distribution,which is closely related to the live of residents,has been greatly tested.How to deal with the high costs,high losses and high emissions in fresh food cold chain logistics distribution has become an urgent problem for the cold chain logistics industry.Therefore,research on vehicle routing is of great practical significance to study the optimization of fresh products with mixed fleet of electric vehicles and fuel vehicles.This article first analyzed the current research status of vehicle routing problems at home and abroad,as well as the development status of new energy vehicles,to determine the research problems and methods.Secondly,relevant theories were elaborated on four key perspectives:vehicle routing problem,solving algorithm,electric logistics vehicle,and cold chain logistics,providing theoretical support for subsequent research.Then,a cold chain logistics distribution mode of hybrid fleet of electric vehicles and fuel vehicles was constructed from the aspects of distribution scenarios,energy replenishment modes and car purchase scheme.The distribution mode of hybrid fleet was optimized by combining time-of-use electricity price and pickup and delivery.Furthermore,considering the time-of-use charging system of social charging stations in real scenarios,a time-sharing pricing function price function was designed.Taking into account relevant constraints such as vehicle load,time window,and driving range,an optimization model for the distribution vehicle path of fresh electric and fuel vehicle mixed fleet considering time-of-use electricity prices was constructed.A hybrid algorithm combining genetic algorithm and variable neighborhood search(GA-VNS)was used to solve the model,and the correctness of the model was verified through case analysis.The impact of changes in electric vehicle load capacity and carbon tax price on the distribution plan of the mixed fleet was further explored.Finally,considering the return and exchange needs of fresh products in actual distribution,with the goal of minimizing the total distribution cost,a vehicle routing optimization model for the mixed fleet of fresh electric and fuel vehicles considering pickup and delivery and time-sharing electricity price was constructed,and a genetic-simulated annealing hybrid algorithm integrating neighborhood search(GASA-NS)was designed.The analysis results of the example showed that the performance of the GASA-NS is superior to the GA-VNS algorithm and GA algorithm.Considering simultaneous pickup and delivery in vehicle routing optimization can improve vehicle loading rate and significantly improve delivery efficiency.The increase in battery capacity of electric vehicles can to some extent weaken the dependence of vehicle routing schemes on charging facilities,effectively reducing distribution costs.With the improvement of battery charging rate,electric logistics vehicles will show greater advantages in urban distribution in the future.This article proposed a cold chain logistics distribution model for a mixed fleet of electric and fuel vehicles,in which the vehicle routing problem for fresh product distribution is optimized by combining time sharing electricity price and pickup and delivery.Some useful references are provided for cold chain logistics enterprises to achieve energy conservation,emission reduction,cost reduction,and efficiency increase in the distribution process.