Research On Optimization Of Vehicle Routing Problem In Xi’an City By M Logistics Company

The rapid development of logistics industry is driven by the rise of e-commerce industry,so logistics industry has become a significant part in part in society.Retailing for 3C electronics online,books,audio and video products,food,daily appliances as well as distribution services are main business of M Logistics Company which is the leader in the logistics industry However,problems such as high costs and low customer satisfaction is faced by M Logistics Company.Therefore,M Logistics Company is selected as the research object on vehicle routing problem in the paper.First of all,for the problems of logistics industry in our country,the factors,characteristics,classifications are summarized clearly.Related theories of customer satisfaction and modeling methods for vehicle routing problem are studied,and the defects as well as superiorities are compared of diverse heuristic algorithms.The content above has led to the definition of the research content and the technical route of this paper.Secondly,in response to the challenges faced by the logistics industry,and the current distribution state of M Logistics Company is analyzed,it founds that the company facing problems of high distribution costs and low customer satisfaction.Thirdly,the improvement of original model is carried out.According to the green logistics development strategy of the company,carbon emission cost is added to the cost function.Regarding to the improvement of low customer satisfaction,the functional relation between fuzzy time window and customer satisfaction is established as the second objective function.To apply unequal restrictions means to convert multi-objective function as single objective function is valid.For the purpose of weakening disadvantages of particle swarm optimization(pso)for slow convergence and low searching efficiency,In This paper,the improving strategies of particle releases and velocity of particle changes dynamically are proposed.In order to test the rationality of the improving strategy,three functions are used to test the new algorithm.The results show that the new algorithm effectively improves the shortcomings of particle swarm optimization.Finally,the improved algorithm is applied to solve the new model.By comparing and analyzing,the conclusion is drawn:the distribution cost of M logistics company reduces by 24.59%,the customer satisfaction increases by 13.67%.It could promote the company develop better,and the research method of this article is a reference to other logistics enterprises.