Research On Logistics Distribution Fleet Configuration And Route Optimization Under Low Carbon

In recent years,electric vehicles,which have small amount of greenhouse gas emissions,low energy consumption and very little noise,are considered to be a green alternative to conventional vehicles.Due to the high purchase cost,limited travelling range and long charging time,it is still difficult for electric vehicles to replace conventional vehicles completely,so mixed fleets where electric vehicles and conventional vehicles coexist are closer to the current situation of logistics enterprises.With the development of related technologies and the strong support of national policies,electric vehicles are maintaining a good momentum of development and are gradually replacing the important position of conventional vehicles in the field of logistics and distribution.Most logistics enterprises usually selectively purchase electric vehicles in small batches to replace the original vehicles gradually.During this process.the technology will upgrade,and the electric fleet will be heterogeneous.Therefore,logistics enterprises should not only continue to pay attention to the cost and timeliness indicators of transportation and distribution.but also face a series of problems caused by various energy sources and models in the process of fleet electrification.This dissertation aims at the fleet configuration in the process of electrification.Comprehensively considering the impact of vehicle’s carbon emissions and charging facilities.this dissertation studies the Bi-objective Mixed Fleet Vehicle Routing Problem with Time Window(BO-MF-VRPTW)and the Bi-objective Heterogeneous Electric Vehicle Routing Problem with Time Window(BO-HE-VRPTW).The main work includes:(1)Study BO-MF-VRPTW.This dissertation considers the impact of vehicle load on energy consumption.costs carbon emissions through carbon tax.And the bi-objective optimization model is established to minimize the total operating cost(including vehicle fixing,transportation,charging and carbon emission cost)and time penalty cost in the distribution process.(2)Study BO-HE-VRPTW.In the construction of its bi-objective optimization model.different types of electric vehicles are considered to be different in terms of load capacity,battery capacity and fixed cost,and the total operating cost and time penalty cost of the heterogeneous electric fleet are minimized.(3)The non-dominated sorting genetic algorithm(NSGA-Ⅱ)is employed to solve the problems.According to the characteristics of the problem,the encoding and decoding strategies are designed respectively.The MATLAB software is employed,and the Pareto front is obtained and compared with the results of the stratified sequencing method and weighted summation method.Through the above solution and comparative analysis,it can be concluded:the two objective functions are contradictory,and the bi-objective optimization is meaningful;the Pareto optimal solution set is within a reasonable range,and there is no dominant and dominated relationship between the Pareto optimal solution set and the solution results of other methods.Therefore,the rationality and validity of the algorithm solution results are verified.This dissertation can provide reference for fleet configuration and driving route optimization in logistics distribution,improves the utilization rate of electric vehicles,helps enterprises reduce operating cost and improve service level,which has important theoretical and practical significance.