Robust multi-market newsvendor models with interval demand data
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.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Wang, Charles X. & Webster, Scott & Suresh, Nallan C., 2009. "Would a risk-averse newsvendor order less at a higher selling price?," European Journal of Operational Research, Elsevier, vol. 196(2), pages 544-553, July.
- Özler, Aysun & Tan, BarIs & Karaesmen, Fikri, 2009. "Multi-product newsvendor problem with value-at-risk considerations," International Journal of Production Economics, Elsevier, vol. 117(2), pages 244-255, February.
- Dutta, Pankaj & Chakraborty, Debjani, 2010. "Incorporating one-way substitution policy into the newsboy problem with imprecise customer demand," European Journal of Operational Research, Elsevier, vol. 200(1), pages 99-110, January.
- Keren, Baruch & Pliskin, Joseph S., 2006. "A benchmark solution for the risk-averse newsvendor problem," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1643-1650, November.
- Chahar, Kiran & Taaffe, Kevin, 2009. "Risk averse demand selection with all-or-nothing orders," Omega, Elsevier, vol. 37(5), pages 996-1006, October.
- Gotoh, Jun-ya & Takano, Yuichi, 2007. "Newsvendor solutions via conditional value-at-risk minimization," European Journal of Operational Research, Elsevier, vol. 179(1), pages 80-96, May.
- Richard L. Daniels & Panagiotis Kouvelis, 1995. "Robust Scheduling to Hedge Against Processing Time Uncertainty in Single-Stage Production," Management Science, INFORMS, vol. 41(2), pages 363-376, February.
- Grubbström, Robert W., 2010. "The Newsboy problem when customer demand is a compound renewal process," European Journal of Operational Research, Elsevier, vol. 203(1), pages 134-142, May.
- Zhang, Bin & Du, Shaofu, 2010. "Multi-product newsboy problem with limited capacity and outsourcing," European Journal of Operational Research, Elsevier, vol. 202(1), pages 107-113, April.
- Taaffe, Kevin & Geunes, Joseph & Romeijn, H. Edwin, 2008. "Target market selection and marketing effort under uncertainty: The selective newsvendor," European Journal of Operational Research, Elsevier, vol. 189(3), pages 987-1003, September.
- Inuiguchi, Masahiro & Sakawa, Masatoshi, 1995. "Minimax regret solution to linear programming problems with an interval objective function," European Journal of Operational Research, Elsevier, vol. 86(3), pages 526-536, November.
- Wang, Charles X. & Webster, Scott, 2009. "The loss-averse newsvendor problem," Omega, Elsevier, vol. 37(1), pages 93-105, February.