Study On Route Optimization Of Electric Refrigerated Vehicles Under Time-varying Networks

With the advancement of China’s urbanization process and the improvement of residents’ overall living standard,people’s consumption of fresh fruits and vegetables and fresh products of novel varieties keeps increasing.The huge consumer market,on the one hand,accelerates the circulation rate of cold chain products and promotes the development of China’s cold chain logistics industry;on the other hand,it also accelerates the speed of energy consumption,increases traffic congestion and environmental pollution.Under the background of advocating energy conservation and environmental protection,pure electric refrigerated vehicles have gradually attracted wide attention from the society and enterprises by virtue of their advantages of "low noise,zero pollution and no traffic restriction".However,due to the shortage of battery technology and the construction of charging and changing facilities at the present stage,the energy replenishment demand of pure electric refrigerated vehicles needs to be considered in the delivery process,and the time is long,which is different from that of traditional fuel vehicles,which can ignore the energy replenishment time on the way.In addition,the energy consumption during the operation of a vehicle is not only related to the distance traveled,but also related to factors such as the speed of the vehicle,which is constantly changing throughout the day,and the weight of the vehicle.Therefore,it is of great practical significance to study the cold-chain logistics distribution problems involving pure electric refrigerated vehicles in combination with time-varying network characteristics,so as to improve the efficiency of cold-chain logistics distribution,reduce distribution costs and promote the green development of cold-chain logistics.Therefore,this paper studies the optimization of the distribution path of electric refrigerated vehicles under the time-varying network,and analyzes the influence of two delivery strategies on the distribution scheme and total distribution cost under the consideration of random customer demands.The specific work is as follows:(1)Study the distribution path optimization problem of electric refrigerated vehicle with static demand under time-varying network.Firstly,the influence of vehicle speed and vehicle weight on the energy consumption of electric refrigerated vehicle was considered,and then the energy consumption of refrigeration equipment was analyzed.In order to satisfy the basic constraints of electric vehicles’ participation in distribution,an optimization model of electric refrigerated vehicles’ distribution path under timevarying network was constructed,and a hybrid heuristic algorithm of mile-saving and tabu search was designed to solve the model.Finally,an example is given to prove the effectiveness of the model and algorithm.(2)Based on the construction of the static demand problem model,the impact of customers’ random demand on the distribution scheme is analyzed.Two delivery strategies,complete delivery and partial delivery,were proposed.By introducing out-ofstock cost into the objective function,an optimization model was established to minimize the total cost including cooling,out-of-stock,cargo damage and charging costs.According to the characteristics of the model,an improved tabu search algorithm is designed.Finally,an example is given to analyze the effects of the two delivery strategies on the delivery scheme,the out-of-stock cost and the total delivery cost under random customer demand,and the effectiveness of the model and algorithm is verified.(3)Verify the model and algorithm through specific cases.Firstly,in the case of static demand,the necessity and effectiveness of considering time-varying network when electric refrigerated vehicles participate in distribution are analyzed.Secondly under uncertainty in customer demand,analysis about the stock quantity of the different distribution scheme and shortage cost and the influence of total distribution cost,on the basis of the analysis to the same requirements meet rate as a benchmark for stock,using different delivery strategy for customer service,to generate the optimal distribution scheme of the relationship between the costs;Finally,through the sensitivity analysis of customer demand fluctuations,the effectiveness of the model and algorithm is verified.