Research On Modeling And Optimization Of Electric Vehicle Routing Problem

With the development of the Internet,urban logistics and distribution increase year by year,the emergence of urban traffic congestion and exhaust pollution and other phenomena,the external diseconomy of urban logistics has aroused everyone's attention.The oil-dominated transportation sector is facing the challenge of resource shortage and environmental pollution worldwide,accelerating the popularization of new energy vehicles is becoming the consensus of the world to achieve sustainable development in the field of transportation.Pushed by the policy that who purchases the new energy vehicles will get a number of subsidies,and the logistics and transport enterprises are required that 30% vehicles must be electric vehicles in the enterprises.China's new energy vehicles,especially the electric vehicles which can achieve zero emissions,because of its high energy efficiency,relatively mature technology are becoming China's new energy vehicle development and transformation of the automotive industry's main strategic direction.As electric vehicles increasingly appear in vehicle scheduling systems,Especially electric taxi dispatching system.Some of the characteristics of electric vehicles,such as: short mileage,long charging time,shortage of charging service facilities and kinetic energy can be converted into electrical energy stored in the capacitor when the electric vehicle is braking,etc.Making the electric vehicle scheduling process need to consider the charging time of electric vehicles,charging station location and electric vehicle capacity constraints.So there is a great impact to the traditional vehicle scheduling theory.The traditional vehicle scheduling theory is not suitable to guide the path planning of electric vehicles.It is urgent to take electric vehicle as the research object of the relevant path planning theory as a theory guide.Based on the existing research,this paper takes electric taxi as the research background,considering the exclusive characteristics of electric taxi,firstly studies the multi-objective electric vehicle routing problem based on the customer satisfaction,which is named as MOEE-VRPTW.The MOEE-VRPTW mixed integer programming model is built.Then,an improved particle swarm optimization(PSO)algorithm is proposed to improve the global search ability of particles by increasing the type of particle sharing information.And the principle of imporved particle swarm optimization is analyzed from the point of view of particle update direction.According to whether the driver is rational,two charging strategies are proposed:(1)the driver is rational person,taskoriented charging strategy is given;(2)the driver is irrational person,the lowest percentage charging strategy is given.And the influence of these two charging strategies on the above model is analyzed,and the application of these two charging strategies is given.The simulation results show that the improved PSO can overcome the shortcomings of the standard particle swarm optimization(PSO)algorithm,which is easy to fall into the local optimum,and improve the performance of the PSO.The parameters and the influence of different charging strategies on the model are analyzed.Finally,based on the MOEE-VRPTW model,a dynamic MOEE-VRPTW model with the customers' information are coming gradually over time,is presented.A time-driven and event-driven rolling horizon scheduling algorithm is proposed to solve this model.The simulation results show that the algorithm can solve the problem quickly.