Research On Distribution Route Optimization Of Multi-model Electric Vehicles In J Company

In recent years,driven by e-commerce,China’s logistics industry has developed rapidly,but the total cost of China’s logistics industry is still on the high side.In addition,customers’ demand for delivery services tends to be personalized,which brings new problems and challenges to logistics enterprises.Due to its advantages of environmental protection,energy saving and low cost,new energy vehicles have gradually been promoted and applied in urban distribution,so it is of great significance to study the distribution path of new energy vehicles.This article analyzes its distribution plan with the current status of Company J,and found that there are some problems when applying for delivery operations in pure electric vehicles,such as unreasonable distribution of models and low loading rates;not timely delivery,increased time costs;distribution staff;The workload is uneven,the distribution efficiency is low,etc.,and later analyzed the influencing factor of the optimization of the distribution path of the company.Based on the above situation,this article conducts research on the optimization of the multi-model electric vehicle distribution path of Company J.Firstly,the distribution route optimization problem of Company J is described,the decision-making objectives and restrictive conditions of the distribution route optimization problem of Company J are determined,and the distribution route optimization model of multivehicle electric vehicles is constructed,aiming at the lowest total distribution cost and comprehensively considering constraints such as service time and workload balance.Secondly,the basic genetic algorithm is improved to solve the model.In order to avoid the problem caused by the deficiency of genetic algorithm itself,multi-point crossover,mutation and reversal operations are used to enhance its search ability.Finally,the actual distribution route of Company J was optimized one day,and the MATLAB software was designed to design the algorithm to find the optimized delivery route.Results showed that the total cost of optimized distribution routes was reduced by 27.41%,and it was better than optimizing the delivery route before the number of vehicles,driving mileage,delay time,and workload standards.Combined with the optimized distribution scheme to make corresponding suggestions to the enterprise,it provides support for the enterprise when improving the distribution plan.At the same time,it can provide other logistics companies with a reference when solving similar problems.