Research On Optimization Of Joint Distribution Lines In Small And Medium-sized Community Chain Supermarkets

With the acceleration of China's urbanization process,the community chain supermarket,which is known as "refined and comprehensive ",is popular with consumers.Logistics distribution is the core competitiveness of chain supermarkets.However,due to the distribution characteristics of "multiple varieties,small batches and high frequency" of small and medium-sized chain supermarkets,it is difficult to form the scale economy of distribution.At the same time,chain supermarkets have strong regional characteristics.In the same area,there are many brands of chain supermarkets coexisting.Many chain supermarkets do not fully consider their own situation.Disregard of the number of stores and the length of distribution routes,they set up their own distribution centers and deliver their own products,which results in the large-scale overlapping and intersection of the distribution network within the same region,and the distribution cost of each company remains high.In view of the above situation,this paper takes Frong Xingsheng chain supermarket and Qianhui supermarket as samples to study on how to reduce logistics cost and improve distribution efficiency by using joint distribution mode for small and medium-sized chain supermarkets.In this thesis,the theory of joint distribution and vehicle path optimization is firstly analyzed.Then,it analyzed the logistics status of Furong Xingsheng supermarket and Qianhui supermarket from the aspects of business scope,commodity characteristics,logistics system and customer distribution,and determined to adopt the entrusted joint distribution mode to optimize its path.In order to verify the effectiveness of joint distribution,the non-cooperative path optimization model and joint distribution path optimization model with the minimum total cost of distribution are respectively established,and bilateral mixed time window is designed for each customer to ensure the delivery service level.Then,the model is solved by designing an improved tabu search method.Considering that the traditional tabu search method is too dependent on the initial solution,the minimum cost interpolation method is adopted in this paper to optimize the path initial solution.Finally,the specific solving process of the algorithm is achieved through python programming.The information of 200 Furong Xingsheng chain supermarkets and 152 Qianhui supermarket stores were collected in this thesis.and k-means clustering for the stores according to the store distance and demand was conducted.The model and algorithm were built to analyze the path optimization examples of two chain supermarkets before and after joint distribution.The results of the calculation show that the total cost of logistics distribution of the enterprises participating in the joint distribution has been greatly reduced and the vehicle loading rate has been improved.This can provide some references for the practice of joint distribution of small and medium-sized chain supermarkets.