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| Content Provider | ACM Digital Library |
|---|---|
| Author | Van Houdt, B. Pérez, J. F. |
| Abstract | We study a supply chain consisting of a single manufacturer and two retailers. The manufacturer produces goods on a make-to-order basis, while both retailers maintain an inventory and use a periodic replenishment rule. As opposed to the traditional (r, S) policy, where a retailer at the end of each period orders the demand seen during the previous period, we assume that the retailers dampen their demand variability by smoothing the order size. More specifically, the order placed at the end of a period is equal to ß times the demand seen during the last period plus (1?ß) times the previous order size, with ß ? (0, 1] the smoothing parameter. We develop a GI/M/1-type Markov chain with only two nonzero blocks $A_{0}$ and $A_{d}$ to analyze this supply chain. The dimension of these blocks prohibits us from computing its rate matrix R in order to obtain the steady state probabilities. Instead we rely on fast numerical methods that exploit the structure of the matrices $A_{0}$ and $A_{d},$ i.e., the power method, the Gauss-Seidel iteration and GMRES, to approximate the steady state probabilities. Finally, we provide various numerical examples that indicate that the smoothing parameters can be set in such a manner that all the involved parties benefit from smoothing. We consider both homogeneous and heterogeneous settings for the smoothing parameters. |
| Starting Page | 30 |
| Ending Page | 30 |
| Page Count | 1 |
| File Format | |
| ISSN | 01635999 |
| DOI | 10.1145/2185395.2185421 |
| Journal | ACM SIGMETRICS Performance Evaluation Review (PERV) |
| Volume Number | 39 |
| Issue Number | 4 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2014-01-10 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Networks and Communications Hardware and Architecture Software |
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