Research On Optimization Of Cigarette Logistics Dist Ribution Path Of A Company

In recent years,logistic industry occupy an increasingly high proportion in enterprises,which is an important way for enterprises to achieve cost reduction and efficiency increase.tobacco industry is no exception.Tobacco is controlled by the state and has the characteristics of unified leadership and monopoly.Meanwhile,the distribution of its retail terminals is complicated and dispersed,which makes the logistics and distribution of tobacco industry special.As the output of cigarettes is limited,it becomes very important to realize cost reduction and efficiency increase from the perspective of logistics.Therefore,how to realize reasonable path planning and design is the key problem of cigarette logistics and distribution.Taking A tobacco company as an example,this paper,by analyzing the actual situation of A tobacco company and according to the special situation of logistics distribution in the tobacco industry,draws A two-stage method of dividing regions first and optimizing routes later.The main contents of the study are as follows:(1)Understands from the current background of the tobacco industry,tobacco cigarette distribution the urgency and importance of path optimization,and then analyze the feasibility of the path planning,based on the interpretation of literature at home and abroad and research analysis,is given in this paper,the research contents,research methods,etc.,and introduces in detail the method and theory related to this article.(2)Through the field research of A company,understand the company’s overall operation process,and focus on the understanding of the distribution center work,the status quo of A company was studied,and the path planning problems of A company were analyzed.(3)According to the actual situation and current problems of Company A,A mu lti-model and single-dispatch center non-loaded model is established.The model aims at minimizing distribution costs and maximizing customer satisfaction.(4)It is planned in two stages.In the first stage,regions were divided,and K-Medoids algorithm was used for clustering according to the actual distance obtained by GPS.At the same time,the limit of vehicle capacity and working time was considered,so that only one vehicle was delivered in each region.The clustering results were fine-tuned according to the actual conditions.And then on to the second stage,before a good area to introduce genetic algorithm for path planning,get the final distribution of the optimized path.Finally,after comparing the optimized path with the original path,it can be concluded that the optimization method in this paper can improve efficiency,reduce cost and improve customer satisfaction to a certain extent,The optimized distribution cost is reduced by 21.6%,and the vehicle loading rate is increased by 25%.At the same time,it provides a reference for solving the distribution path problem with similar characteristics.