BROWSE

Related Researcher

Author's Photo

Lee, Soonhui
School of Business Administration
Research Interests
  • Production and logistics
  • Optimization under uncertainty
  • Healthcare Management, Revenue Management

ITEM VIEW & DOWNLOAD

Newsvendor-type models with decision-dependent uncertainty

Cited 4 times inthomson ciCited 4 times inthomson ci
Title
Newsvendor-type models with decision-dependent uncertainty
Author
Lee, SoonhuiHomem-de-Mello, TitoKleywegt, Anton J.
Keywords
Data-driven optimization; Newsvendor model; Stochastic approximation
Issue Date
2012-10
Publisher
SPRINGER HEIDELBERG
Citation
MATHEMATICAL METHODS OF OPERATIONS RESEARCH, v.76, no.2, pp.189 - 221
Abstract
Models for decision-making under uncertainty use probability distributions to represent variables whose values are unknown when the decisions are to be made. Often the distributions are estimated with observed data. Sometimes these variables depend on the decisions but the dependence is ignored in the decision maker's model, that is, the decision makermodels these variables as having an exogenous probability distribution independent of the decisions, whereas the probability distribution of the variables actually depend on the decisions. It has been shown in the context of revenue management problems that such modeling error can lead to systematic deterioration of decisions as the decision maker attempts to refine the estimates with observed data. Many questions remain to be addressed. Motivated by the revenue management, newsvendor, and a number of other problems, we consider a setting in which the optimal decision for the decision maker's model is given by a particular quantile of the estimated distribution, and the empirical distribution is used as estimator. We give conditions under which the estimation and control process converges, and showthat although in the limit the decision maker's model appears to be consistent with the observed data, the modeling error can cause the limit decisions to be arbitrarily bad.
URI
Go to Link
DOI
10.1007/s00186-012-0396-3
ISSN
1432-2994
Appears in Collections:
SBA_Journal Papers
Files in This Item:
2-s2.0-84867278770.pdf Download

find_unist can give you direct access to the published full text of this article. (UNISTARs only)

Show full item record

qrcode

  • mendeley

    citeulike

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

MENU