Optimal Inventory Policies when the Demand Distribution is not Known /
This paper analyzes the stochastic inventory control problem when the demand distribution is not known. In contrast to previous Bayesian inventory models, this paper adopts a non-parametric Bayesian approach in which the firm's prior information is characterized by a Dirichlet process prior. Th...
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| Muut tekijät: | , |
| Aineistotyyppi: | Aikakauslehti |
| Kieli: | English |
| Julkaistu: |
Washington, D.C. :
International Monetary Fund,
2000.
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| Sarja: | IMF Working Papers; Working Paper ;
No. 2000/183 |
| Aiheet: | |
| Linkit: | Full text available on IMF |
| Yhteenveto: | This paper analyzes the stochastic inventory control problem when the demand distribution is not known. In contrast to previous Bayesian inventory models, this paper adopts a non-parametric Bayesian approach in which the firm's prior information is characterized by a Dirichlet process prior. This provides considerable freedom in the specification of prior information about demand and it permits the accommodation of fixed order costs. As information on the demand distribution accumulates, optimal history-dependent (s,S) rules are shown to converge to an (s,S) rule that is optimal when the underlying demand distribution is known. |
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| Huomautukset: | <strong>Off-Campus Access:</strong> No User ID or Password Required <strong>On-Campus Access:</strong> No User ID or Password Required |
| Ulkoasu: | 1 online resource (24 pages) |
| Aineistotyyppi: | Mode of access: Internet |
| ISSN: | 1018-5941 |
| Pääsy: | Electronic access restricted to authorized BRAC University faculty, staff and students |