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Department of Business and Management Science, Norwegian School of Economics (NHH) Discussion Papers, Department of Business and Management Science, Norwegian School of Economics (NHH)

No 2011/14:
A maximum entropy approach to the newsvendor problem with partial information

Jonas Andersson (), Kurt Jörnsten (), Sigrid Lise Nonås (), Leif K. Sandal () and Jan Ubøe ()

Abstract: In this paper, we consider the newsvendor model under partial information, i.e., where the demand distribution D is partly unknown. We focus on the classical case where the retailer only knows the expectation and variance of D. The standard approach is then to determine the order quantity using conservative rules such as minimax regret or Scarf's rule. We compute instead the most likely demand distribution in the sense of maximum entropy. We then compare the performance of the maximum entropy approach with minimax regret and Scarf's rule on large samples of randomly drawn demand distributions. We show that the average performance of the maximum entropy approach is considerably better than either alternative, and more surprisingly, that it is in most cases a better hedge against bad results.

Keywords: Newsvendor model; entropy; partial information; (follow links to similar papers)

JEL-Codes: C00; (follow links to similar papers)

30 pages, August 31, 2011

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