Robust multi-market newsvendor models with interval demand data. (English) Zbl 1237.90016

Lin, Jun; Ng, Tsan Sheng

Eur. J. Oper. Res. 212, No. 2, 361-373 (2011).

Summary: 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.

MSC:

90B05	Inventory, storage, reservoirs
90B50	Management decision making, including multiple objectives
90C59	Approximation methods and heuristics in mathematical programming

Keywords:

risk analysis; newsvendor problem; minimax regret; uncertainty modeling

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