Design And Implementation Of The Electric Vehicles Logistics Distribution Operation Scheduling Model

The development of green logistics and electric vehicles has effectively promoted the application of electric vehicles in the field of logistics distribution. However, the limited cruising range of electric vehicles and a few charging facilities have posed some difficulties and challenges to the vehicle scheduling optimization of the logistics distribution. Up to now, researches of the EVRP have mainly focused on the static EVRP while researches of the dynamic EVRP, especially the time dependent EVRP are still scarce. In addition, it is rare that the path planning is introduced to calculate the travel time and charge consumption in solving the EVRP model. In order to solve these problems, the time dependent EVRP model was built, and the solution algorithm was designed to solve this model and the vehicle scheduling prototype system was designed and implemented in the background of the electric vehicles logistics distribution.Firstly, the time dependent EVRP was expounded and energy consumption characteristics of electric vehicles were analyzed, as well as time dependent characteristics of road network. The time dependent EVRP model was built based on the EVRP model through introducing the time dependent characteristic. Secondly, the solution algorithm was analyzed based on the study of the time dependent EVRP model. The annular road network generating algorithm was designed to realize the simulation of the road network. The annular road network and the same scale random network were compared and analyzed. The whole framework of the solution algorithm was established based on the traditional grouping genetic algorithm and the improved grouping genetic algorithm was designed through introducing the generating algorithm of the initial solution combining the greedy construction heuristic with the random approach, the improved A-star algorithm combing the time dependent characteristic with the energy consumption characteristic and the regional searching algorithm. The time dependent EVRP model was solved by the solution algorithm, and the improved grouping genetic algorithm and the traditional grouping genetic algorithm were compared and analyzed. Lastly, the electric vehicles scheduling prototype system was designed and implemented based on the early results. The business process of electric vehicles logistics distribution was analyzed. Modules and the database schema of the prototype system were designed and the technical framework was established. In addition, main pages of the prototype sys-tem were displayed. In conclusion, building the model and implementing the algorithm of the time dependent EVRP can get closer to the actual logistics distribution, improve the logistics efficiency and enrich the theory and application research of the vehicle routing problem.