Milk-run Mode Research Articles

Research on Vehicle Routing Problem in Auto Parts Inbound Logistics Based on Milk Run Mode

The application of milk run in domestic automobile parts supply was studied. A mathematical model for routing a milk run system was formulated by minimizing the transportation and inventory cost under the restriction of tiered storage pricing scheme and multiple vehicle types. In solving the model, a modified genetic algorithm was developed, which is suitable for realistic sized problems. The utility of the approach was demonstrated through a computational experiment.

An integrated inbound logistics mode with intelligent scheduling of milk-run collection, drop and pull delivery and LNG vehicles

Although it provides a feasible inbound logistics solution for steady production and low inventory management, the Milk-run mode inevitably leads to a high transportation costs due to the features of small-batch and high-frequency delivery. In order to break through the defections of the existing inbound logistics mode, an integrated inbound logistics (IIL) mode with low-carbon and high efficiency is established. An intelligent scheduling method combines Milk-run collection with drop and pull delivery together. Moreover, the LNG vehicles are simultaneously used in the whole process. With AJ company’s auto-parts inbound logistics as a case, the IIL mode is formulated with a mixed integer mathematical model. The genetic algorithm coded with Matlab is used to find the optimal solution. The results show that when compared with the original Milk-run mode, the IIL mode brings massive reductions in driving mileage, wait time and waste gas emission. It can make significant benefits in both economic and social sense. Therefore, it is entirely reasonable for management of industries to believe that the IIL mode will be a feasible and promising alternative for inbound logistics.

Study on Multi-Depot Collaborative Transportation Problem of Milk-Run Pattern

Analyze the relevance between Milk Run mode and collaborative transportation problem, put forward collaborative transportation problem of multiple-depot on Milk Run mode under the supply and demand separate nodes, consider the value of transport and transport costs, introduce the concept of node - arc flow, by comparing the size of traffic flow determine nodes collection, and then constructed multi-transport model of the problem. Considering one-way pickup and delivery closed, construct two-stage algorithm model, use dynamic programming recursive solution to determine the best route to pick up, and then solving delivery routing problem with different start and return point based on geometric method of Cosine. Finally use a numerical example illustrates the effectiveness of the algorithm and reasonable model.

带卸货时间窗的循环取货路径计划问题研究

当今汽车供应链拉动式生产盛行，汽车零部件入厂物流表现出高度的复杂性和专业性，针对该场景下的循环取货问题，引入卸货时间窗的概念，设计供应商集货需求可拆分的数学模型，以降低零部件循环取货过程中的车辆运输成本，同时满足卸货时间窗和车辆容量的限制。根据所设计模型的特点设计禁忌搜索算法，改进初始解及邻域搜索算法，最后通过实验数据证明算法的有效性，并与现有算法进行比对，表明该模式下的循环取货模式可以更有效的节约运输成本，保证生产效率。 Nowadays, pulling type production becomes more popular in automobile supply chain. Inbound logistics of auto parts showed a high degree of complexity and professionalism. For the milk-run problem in such scene, this paper designs a model with unload time window and split deliveries, to minimize the transportation cost. According to the characteristics of the model, this paper designed a tabu search algorithm, and the initial solution and the neighborhood search algorithm are improved. Finally, it proved the validity of the algorithm by the experimental data, and compared with the existing algorithms. The result shows that the milk-run mode can effectively save transportation cost and ensure production efficiency.

The Study in Supply Chain of Auto Parts Based on Milk-Run

With the rapid development of the domestic economy, the output of the automobile industry is growing dramatically. The increasing number of the suppliers, auto parts and their categories has brought more challenges to the third party automobile logistics provider with requirements of better service mode and quality. The poor optimal state of the original delivery route and low vehicle loading rate have a huge impact on the production effectiveness. Thus, according to this problem, a virtual automobile factory has been set with specific auto parts orderings with the purpose of optimizing the delivery route and rising the vehicle loading rate. Combining with the location of the picking points, transport frequency and the loading capacity of each vehicle, taboo search algorithm has been applied to the milk-run mode to help develop a better delivery route for the logistic company.

Planning of Production, Inventory and Logistics with Direct Shipment and Milk run Strategies: Numerical Experiment

We study a supply chain comprised of a manufacturer owning multiple production lines and a warehouse, and multiple retailers buying from the manufacturer. The manufacturer can choose whether to send products to the retailers directly from loading area using direct shipment or send the product to be stored at the warehouse. If the demand is satisfied from the warehouse, the company can choose the logistic strategy. The company can send the product from the warehouse to a retailer using a direct shipment mode (a truck only visits the retailer) or using milk run mode (a truck visits multiple retailers in a single trip). We develop a mixed integer programming model to find the optimal decisions for production quantities at each production line, the quantities of inventories at the loading area, the warehouse and the retailers, and the transportation strategies to deliver products to retailers in every period. We conduct numerical experiments and then analyze the results. Many managerial insights are drawn for practitioners. Several optimal transportation strategies are observed by mixing between a temporal demand aggregation strategy, the milk run strategy and the direct shipment strategy.