Article ID: | iaor20042458 |
Country: | Netherlands |
Volume: | 126 |
Issue: | 1 |
Start Page Number: | 21 |
End Page Number: | 41 |
Publication Date: | Feb 2004 |
Journal: | Annals of Operations Research |
Authors: | Gallego Guillermo, Hu Haichao |
Keywords: | markov processes |
In many production/inventory systems, not only is the production/inventory capacity finite, but the systems are also subject to random production yields that are influenced by factors such as breakdowns, repairs, maintenance, learning, and the introduction of new technologies. In this paper, we consider a single-item, single-location, periodic-review model with finite capacity and Markov modulated demand and supply processes. When demand and supply processes are driven by two independent, discrete-time, finite-state, time-homogeneous Markov chains, we show that a modified, state-dependent, inflated base-stock policy is optimal for both the finite and infinite horizon planning problems. We also show that the finite-horizon solution converges to the infinite-horizon solution.