Minmax regret combinatorial optimization problems with ellipsoidal uncertainty sets

Chassein, André and Goerigk, Marc (2017) Minmax regret combinatorial optimization problems with ellipsoidal uncertainty sets. European Journal of Operational Research, 258 (1). pp. 58-69. ISSN 0377-2217

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We consider robust counterparts of uncertain combinatorial optimization problems, where the difference to the best possible solution over all scenarios is to be minimized. Such minmax regret problems are typically harder to solve than their nominal, non-robust counterparts. While current literature almost exclusively focuses on simple uncertainty sets that are either finite or hyperboxes, we consider problems with more flexible and realistic ellipsoidal uncertainty sets. We present complexity results for the unconstrained combinatorial optimization problem, the shortest path problem, and the minimum spanning tree problem. To solve such problems, two types of cuts are introduced, and compared in a computational experiment.

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Journal Article
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European Journal of Operational Research
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This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 258, 1, 2017 DOI: 10.1016/j.ejor.2016.10.055
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Deposited On:
03 Nov 2016 09:04
Last Modified:
18 Sep 2023 01:07