关键词: 共同客户, 协同配送, 客户聚类, 蚁群算法

Abstract: In the last kilometer of distribution, there is a situation where some distribution centers may provide distribution services to a particular public area or some co-customers at the same time, i.e. some customers require only one distribution center to provide distribution services, while some customers require multiple distribution centers to provide distribution services (customers who need multiple distribution centers to provide services are co-customers of the enterprise). When there are co-customers, the distribution routes of the two distribution centers will produce coupling(coupling points are common customer points), which leads to a great negative impact, such that repeated cross-over of distribution routes lead to high logistics transportation costs, low vehicle utilization, and traffic congestion; logistics service levels do not meet customer satisfaction standards and so on. Therefore, how to deal with the problem of inter-enterprise mutual customers is the key. This paper considers the situation of common customers in the distribution process, and puts forward the problem of considering the co-vehicle path of the common customer. Considering the collaborative vehicle routing problem of common customers, we can evaluate the potential benefits of cooperation between independent distribution centers. By calculating and comparing the benefits of each independent distribution center before and after cooperation, each independent distribution center may urge them to form a strategic cooperative relationship and make a cooperation plan. At the same time, the model can also be used to optimize the cooperation between existing enterprises.
The main research work of this paper is as follows: (1)In order to solve the situation of common customers, from the point of view of enterprises and customers, a kind of multi-distribution center and time window restrictions of VRP model is proposed. From the point of the enterprise, each distribution center is no longer limited to its own distribution customers. At the same time, from the customer's point of view, in order to meet the customer's requirements for time window and service quality, this paper takes the target function in the introduction of the penalty function into consideration. (2)The two-stage heuristic algorithm “classification before solution” is used to solve the problem. In the first stage, the algorithm of customer clustering using the transfer rules of ant colony algorithm is proposed, which classifies the common customers based on the distribution center, that is, the customers who are in need of multiple distribution centers are transferred to a distribution center to complete the distribution. In the second stage, the improved ant colony algorithm is used to solve the situation of each garage.
In order to evaluate the cost savings generated by this model, the results of the collaborative scheme and the results of the non-collaborative scheme are compared. The results show that the two schemes are basically consistent in terms of vehicle usage and average vehicle utilization, but under the collaborative scheme, both the cost of the respective distribution center and the overall cost of synergy are reduced in a certain degree. This shows that multi-distribution center coordination can reduce the distribution cost of the whole logistics system, which proves the rationality and effectiveness of the model.

Key words: common customers, collaborative distribution, customer clustering, ant colony algorithms