Electric Vehicle Routing Optimization Problem Based On Joint Distribution Of Urban Logistics

For a long time,the use of traditional vehicles fueled by fossil energy has brought convenience to people,but it also caused a series of energy and environmental problems,which also promoted the development of low-emission new energy vehicles such as electric vehicles.In order to keep up with the trend of the times,logistics companies have gradually begun to pay attention to the application of electric vehicles in logistics and distribution in the process of development and transformation.In addition,China's urban logistics system currently has problems such as low degree of informatization,low distribution efficiency,and low resource utilization rate,which is not equal to the continuous development of China's urban economy.Therefore,the management of logistics enterprises and the rational allocation of distribution resources have become the key to green and intelligent urban logistics distribution.Based on the above two aspects,this paper first reviews the related research on vehicle routing problems and joint distribution at home and abroad,and combines relevant theories and methods,and proposes the electric vehicle to carry out the joint distribution of urban logistics,which is necessary for changing the city of logistics sub-distribution mode of traditional logistics enterprises,rational using of distribution resources,and reduction of urban air pollution;secondly,by analyzing the electric vehicle path optimization model with time window and the vehicle routing optimization model of joint distribution,and combining of two models' characteristics,we create the electric vehicle path optimization model based on joint distribution,which minimize the total cost including fixed cost,transportation cost and penalty cost is minimum.Then we analyzed and compared the commonly used solving algorithms in vehicle routing problem.The genetic algorithm for large-scale complex problems is selected to solve the model in this paper,and the basic flow of the genetic algorithm is analyzed.At the same time,the process of coding,selection,crossover and mutation of genetic algorithm are made the corresponding design by the characteristics of the model.The the feasibility of the model and algorithm is verified by a specific example.Finally,the research results are summarized,and the problems and limitations of the research are discussed.The next research and work are also expected.