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Title: Robust regret for uncertain linear programs with application to co-production models
Authors: Ng, T.S. 
Keywords: Linear programming
Minimax regret
Uncertainty modelling
Issue Date: 2013
Citation: Ng, T.S. (2013). Robust regret for uncertain linear programs with application to co-production models. European Journal of Operational Research 227 (3) : 483-493. ScholarBank@NUS Repository.
Abstract: This paper considers the regret optimization criterion for linear programming problems with uncertainty in the data inputs. The problems of study are more challenging than those considered in previous works that address only interval objective coefficients, and furthermore the uncertainties are allowed to arise from arbitrarily specified polyhedral sets. To this end a safe approximation of the regret function is developed so that the maximum regret can be evaluated reasonably efficiently by leveraging on previous established results and solution algorithms. The proposed approach is then applied to a two-stage co-production newsvendor problem that contains uncertainties in both supplies and demands. Computational experiments demonstrate that the proposed regret approximation is reasonably accurate, and the corresponding regret optimization model performs competitively well against other optimization approaches such as worst-case and sample average optimization across different performance measures. © 2012 Elsevier B.V. All rights reserved.
Source Title: European Journal of Operational Research
ISSN: 03772217
DOI: 10.1016/j.ejor.2013.01.014
Appears in Collections:Staff Publications

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