Quantifying the effectiveness of VMI and integrated inventory management in a supply chain with uncertain lead-times and uncertain demands |
| |
Authors: | Dong-Ping Song John Dinwoodie |
| |
Affiliation: | 1. International Shipping and Logistics Group , University of Plymouth Business School , Plymouth, UK dongping.song@plymouth.ac.uk;3. International Shipping and Logistics Group , University of Plymouth Business School , Plymouth, UK |
| |
Abstract: | This article considers the inventory management problem in a supply chain with uncertain replenishment lead-times and uncertain demands. The optimal integrated inventory management (IIM) policy is developed using stochastic dynamic programming theory. The IIM policy is contrasted with two pull-type vendor-managed inventory policies (VMI-1 and VMI-2) and a traditional retailer-managed inventory policy (RMI). Computational results show that in such stochastic supply chains, IIM performs about 23, 15, and 3% better than the optimised RMI, VMI-1 and VMI-2 policies, respectively, while two VMI policies are about 8 and 20% better than the best RMI. The basestock-based VMI-2 is a very good form of VMI. The ANOVA analysis reveals that the replenishment lead-times have the largest effect on the relative performance between IIM and other policies. Numerical examples demonstrated that the IIM policy has good structural properties and can be characterised by a set of switching curves. |
| |
Keywords: | inventory management supply chain uncertainty vendor-managed inventory stochastic dynamic programming |
|
|