Operations Research and Management Science ›› 2023, Vol. 32 ›› Issue (3): 104-110.DOI: 10.12005/orms.2023.0087

• Theory Analysis and Methodology Study • Previous Articles     Next Articles

An Optimization Approach of Collaborative Distribution Considering Common Customers

LI Mengtao, DING Qiulei, LIU Kaijun   

  1. School of Business Administration, Dongbei University of Finance & Economics, Dalian 116025, China
  • Received:2021-01-11 Online:2023-03-25 Published:2023-04-25

考虑共同客户的协同配送优化方法研究

李孟涛, 丁秋雷, 柳凯军   

  1. 东北财经大学 工商管理学院,辽宁 大连 116025
  • 作者简介:李孟涛( 1974-) ,男,黑龙江大庆人,讲师,博士,研究方向:物流与供应链管理。
  • 基金资助:
    国家社会科学基金重大项目(18ZDA058);国家社会科学基金重点项目(22AGL033);辽宁省教育厅科学研究经费项目(LN2020J04)

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

摘要: 本文针对一些客户仅需要一个配送中心提供配送服务,而某些客户需要多个配送中心提供配送服务(需要多个配送中心提供服务的客户就是企业的共同客户)的情形,提出了一类具有多配送中心、有时间窗限制的车辆路径问题,建立了相应的数学模型。基于“先分类,后求解”的思想,本文设计了两阶段启发式算法:第一阶段提出基于客户聚类的启发式算法,形成聚类信息,将多中心问题转化成单中心问题;第二阶段通过改进的蚁群算法对每个配送中心的情况进行求解。最后,通过算例对该模型的可行性和有效性进行了验证,结果表明与非协同配送方式相比,在配送距离、降低配送成本、提高客户满意度等方面均有明显改进。

关键词: 共同客户, 协同配送, 客户聚类, 蚁群算法

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