| In recent years,people’s growing needs for a better life have led to a sharp increase in logistics activities,and logistics has become an indispensable part of social and economic activities.But it also inevitably brings problems such as traffic congestion,environmental pollution and non-renewable energy consumption.In order to alleviate the pressure caused by the shortage of oil resources,global warming and noise pollution,the government has introduced a number of welfare policies to provide convenience for enterprises using electric vehicles for logistics and distribution activities.On the other hand,it has strengthened supporting infrastructure such as charging stations.Due to the incentives of the new policy and the constraints of emission reduction targets,many companies including JD.com and SF Express have begun to use electric vehicles to replace traditional fuel vehicles to complete their logistics and distribution tasks.The limited cruising range of electric vehicles greatly increases the possibility of going to charging stations during delivery.How to plan the distribution path of electric vehicles to reduce costs and increase efficiency has become one of the important research topics in the logistics industry.Aiming at the increasingly prominent traffic congestion problem,this paper proposes an Electric Vehicle Routing Problem with Time-varying Traffic Congestion considering congestion factors,considering the nonlinear influence of EV driving speed and real-time load on power consumption,and allowing partial charging strategy in EV distribution based on different charging technology perspectives.Firstly,an EVRP model that allows partial charging and linear power consumption is constructed without considering congestion.On this basis,the nonlinear power consumption of the electric vehicle and the driving time of the electric vehicle under congestion constraints are modeled respectively,with the goal of minimizing the delivery distance,the EVRP model of random congestion and the EVRP of time-varying congestion are constructed respectively.Secondly,a two-stage heuristic algorithm is designed to solve the model.In the algorithm design,the first stage uses the C-W saving algorithm combined with the greedy algorithm idea to construct the initial solution;the second stage uses the tabu search algorithm to improve the initial solution.We designed four kinds of inter-path movement operators and two kinds of intra-path movement operators to enhance the neighborhood search ability,and optimized the decision of customers and charging stations by considering the nonlinear power consumption under the congestion mechanism in the neighborhood search.Finally,the improved Solomon benchmark instances are used to generate examples of different scales,which are compared with the initial solution in the vertical direction,and compared with the local search algorithm based on the simulated annealing framework in the horizontal direction to verify the feasibility and effectiveness of the proposed algorithm.By analyzing the influence of the changes in the parameter values of the EVRP model,such as battery capacity,charging rate and the number of charging stations,on the results of the model,it is proved that the algorithm has certain application value.The experimental results show that the performance of the algorithm is good in the test examples,the increase of battery capacity and charging rate will have a positive impact on the results to varying degrees,and the change of the number of charging stations has no obvious trend on the results and no obvious impact on the operating efficiency of the algorithm. |
