Impact of Demand Probability Distributions and Direct Deliveries on a Hybrid Transshipment Model of Prototype Parts in the Automotive Industry

Prototype parts logistics in the automotive industry is characterized by unique parts and logistics networks with different warehouse locations. The future assembly location of the prototype parts is unknown. However, as soon as the assembly location is known, the prototype parts must be delivered to the customer at short notice. Weckenborg et al. (2024) have developed a hybrid transshipment model for these characteristics in a hub and spoke network. In the model reactive transshipments will be used to transship other unique parts proactive to different warehouses. For the decision on proactive transshipments, approximated future shipping costs are introduced for each part in each warehouse. The approximated future shipping costs are calculated based on the fixed transportation costs and the demand probabilities. In the following numerical study, the influence of different demand probability distributions and the switch from a hub and spoke network to direct deliveries to the various locations on the hybrid approach is analyzed. The study shows that a demand probability distribution with a high demand probability for one customer can reduce transportation costs. The results of the numerical study also show that the number of proactive transshipped parts can be drastically reduced if parts are delivered directly from the supplier to the warehouse with the lowest approximated future shipping costs depending on the demand probabilities.