A new bound for the midpoint solution in minmax regret optimization with an application to the robust shortest path problem

Minmax regret optimization aims at finding robust solutions that perform best in the worst-case, compared to the respective optimum objective value in each scenario. Even for simple uncertainty sets like boxes, most polynomially solvable optimization problems have strongly NP-complete minmax regret counterparts. Thus, heuristics with performance guarantees can potentially be of great value, but only few such guarantees exist.

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Year of publication:	2015
Authors:	Chassein, André B. ; Goerigk, Marc
Published in:	European Journal of Operational Research. - Elsevier, ISSN 0377-2217. - Vol. 244.2015, 3, p. 739-747
Publisher:	Elsevier
Subject:	Combinatorial optimization \| Minmax regret \| Robust optimization \| Approximation \| Robust shortest paths

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011264336