Verfügbarkeit: Optimal Inventory Policies When the Demand Distribution is Not Known

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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1. Verfasser:	Larson, Erik W. (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Washington, D.C International Monetary Fund 2000
Schriftenreihe:	IMF Working Papers Working Paper No. 00/183
Online-Zugang:	UBW01 UEI01 LCO01 SBR01 UER01 SBG01 UBG01 FAN01 UBT01 FKE01 UBY01 UBA01 FLA01 UBM01 UPA01 UBR01 FHA01 FNU01 BSB01 TUM01 Volltext
Zusammenfassung:	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
Beschreibung:	1 Online-Ressource (24 p)
ISBN:	1451859309 9781451859300

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spelling	Larson, Erik W. Verfasser aut Optimal Inventory Policies When the Demand Distribution is Not Known Larson, Erik W Washington, D.C International Monetary Fund 2000 1 Online-Ressource (24 p) txt rdacontent c rdamedia cr rdacarrier IMF Working Papers Working Paper No. 00/183 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 Online-Ausg Olson, Lars J. Sonstige oth Sharma, Sunil Sonstige oth http://elibrary.imf.org/view/IMF001/05056-9781451859300/05056-9781451859300/05056-9781451859300.xml Verlag URL des Erstveröffentlichers Volltext
spellingShingle	Larson, Erik W. Optimal Inventory Policies When the Demand Distribution is Not Known
title	Optimal Inventory Policies When the Demand Distribution is Not Known
title_auth	Optimal Inventory Policies When the Demand Distribution is Not Known
title_exact_search	Optimal Inventory Policies When the Demand Distribution is Not Known
title_exact_search_txtP	Optimal Inventory Policies When the Demand Distribution is Not Known
title_full	Optimal Inventory Policies When the Demand Distribution is Not Known Larson, Erik W
title_fullStr	Optimal Inventory Policies When the Demand Distribution is Not Known Larson, Erik W
title_full_unstemmed	Optimal Inventory Policies When the Demand Distribution is Not Known Larson, Erik W
title_short	Optimal Inventory Policies When the Demand Distribution is Not Known
title_sort	optimal inventory policies when the demand distribution is not known
url	http://elibrary.imf.org/view/IMF001/05056-9781451859300/05056-9781451859300/05056-9781451859300.xml
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