Research On Weighted Electric Vehicle Routing Problem With Soft Time Windows

In recent years,with the rapid development of the logistics industry and the rapid growth of logistics vehicles,the problems of energy consumption and environmental pollution have become increasingly prominent.The unique low consumption,low emissions and low pollution characteristics of electric vehicles have become an effective way to solve this problem.Therefore,the country has issued a series of policies and measures to promote the development of the electric vehicle industry and its supporting service facilities and equipment.The leaders of logistics industries such as JD.com and Alibaba are also responding to the needs of the times and vigorously implement the electrification of vehicles.Electric vehicles are the mainstream development trend of logistics distribution vehicles in the future.Electric vehicles consume power during the driving distance.The distance traveled by an electric vehicle is closely related to its battery energy consumption during driving.Therefore,battery energy consumption is one of the issues that must be considered in the path optimization of electric vehicles.In the path optimization problem of electric vehicles,for the energy consumption of batteries,most scholars currently only consider the impact of driving distance on battery energy consumption,ignoring the impact of cargo load on battery energy consumption,resulting in actual power consumption and theory during vehicle travel,there is a deviation,which makes the battery power insufficient to support the electric vehicle to reach the charging station or distribution center,which in turn affects the scientificity of solving the electric vehicle distribution path.Therefore,this paper proposes to consider the path planning problem under cargo load,the specific work is as follows:1.In view of the current research status of electric vehicle path optimization at home and abroad,this article introduces the cargo load factor into the objective function,and establishes a path optimization model that considers the cargo load;on the other hand,considering the complexity of the actual distribution process,and the The long charging time of the vehicle at the charging station will make it difficult for the vehicle to strictly meet the requirements of each customer's receipt time window,that is,the soft time window constraint.Based on the consideration of these two factors,the electric vehicle path optimization scheme is designed,and finally the path optimization model of this problem is constructed.2.In terms of solving algorithm,this paper improves the genetic algorithm in combination with the soft time window path optimization model considering cargo load.In order to maintain the diversity of the population and prevent premature convergence of the solution results,the crossover operator is improved in the paper,and the elite reservation is integrated into the selection operation.Strategy.In order to prevent the genetic algorithm from falling into the local minimum,the hill climbing algorithm is placed as an independent operator.3.Based on the calculation example,MATLAB is used to solve and simulate the soft-window electric vehicle path optimization model constructed by this paper considering the cargo load and the improved genetic algorithm.The optimal distribution route of this paper is obtained,and the model and the paper are verified.The scientific nature of the algorithm.Through in-depth analysis of algorithm comparison,remaining power and time window factors,the applicability and effectiveness of the model and solving algorithm are verified.Finally,the sensitivity was analyzed to prove the influence of battery capacity and maximum cargo load on the path planning of electric vehicles.