Low Carbon Path Optimization Problem Based On Electric Vehicle Logistics Distribution

With the public attention to the environment and the development of e-commerce,Logistics industry is facing new requirements for distribution.As we all know,logistics industry has an important influence on carbon emission.so Green logistics,low carbon travel will be the normal of public life and Industry operating.Compared with traditional vehicles,electric vehicles are characterized by low energy consumption and small pollu-tion,Therefore,the application of electric vehicles to logistics operation has become the focus of various scholars.At present,Electric cars are still in the development stage and the supporting infrastructure are still not perfect,the most important problem is the short range.Based on these problems,this paper combines the characteristics of electric logistics vehicles,consider-ing the endurance capacity,loading quantity and speed of electric vehicles,take aim of minimize carbon emissions and shortest path,carry on an investigation into vehicle routing problem for electric vehicles.The main tasks are as follows:(1)Refer to conventional vehicles for calculating carbon emiss-ions,analyze the characteristics of Electric power distribution electric vehicle,considering the impact of speed and load on carbon emis-sion,then,a carbon emission calculation method for Electric vehicle for electric change is proposed.(2)Construct Low carbon route optimization model of logistics distribution based on electric vehicle.With less carbon emission and shortest path to optimize the target to determine the delivery order of vehicles.In the middle of the distribution,we consider the battery life of pure electric vehicles,the dynamic change of the battery and the running time.An electric vehicle search strategy adapted to the model is proposed(3)Design an adaptive genetic algorithm based on hill-climbing search for electric vehicles,An algorithm are introduced Based on the character-ristics of the model.Hill climbing search algorithm and adaptive crossover and mutation operator are introduced and the improved genetic algorithm is used to solve and analyze the model.(4)Taking a LTL express enterprise as an example,put operational data into the model,used improved genetic algorithm to determine the optimal path of total cost minimization and the data analysis is obtained that carbon emissions are proportional to the speed of electric vehicles and directly proportional to it.The faster the electric car,the more carbon emissions;The heavier the load,the more carbon emissions.We also compared and analyzed about the convergence of the algorithm and the iteration number of the optimal solution,find that the improved genetic algorithm has good convergence and efficiency improvement.