Please use this identifier to cite or link to this item:
Title: Robust multi-market newsvendor models with interval demand data
Authors: Lin, J.
Ng, T.S. 
Keywords: Minimax regret
Newsvendor problem
Risk analysis
Uncertainty modeling
Issue Date: 16-Jul-2011
Citation: Lin, J., Ng, T.S. (2011-07-16). Robust multi-market newsvendor models with interval demand data. European Journal of Operational Research 212 (2) : 361-373. ScholarBank@NUS Repository.
Abstract: We present a robust model for determining the optimal order quantity and market selection for short-life-cycle products in a single period, newsvendor setting. Due to limited information about demand distribution in particular for short-life-cycle products, stochastic modeling approaches may not be suitable. We propose the minimax regret multi-market newsvendor model, where the demands are only known to be bounded within some given interval. In the basic version of the problem, a linear time solution method is developed. For the capacitated case, we establish some structural results to reduce the problem size, and then propose an approximation solution algorithm based on integer programming. Finally, we compare the performance of the proposed minimax regret model against the typical average-case and worst-case models. Our test results demonstrate that the proposed minimax regret model outperformed the average-case and worst-case models in terms of risk-related criteria and mean profit, respectively. © 2011 Elsevier B.V. All rights reserved.
Source Title: European Journal of Operational Research
ISSN: 03772217
DOI: 10.1016/j.ejor.2011.01.053
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Aug 13, 2018


checked on Aug 13, 2018

Page view(s)

checked on Jun 1, 2018

Google ScholarTM



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