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math.OC2018

Algorithms and Uncertainty Sets for Data-Driven Robust Shortest Path Problems

André Chassein, Trivikram Dokka, Marc Goerigk

We consider robust shortest path problems, where the aim is to find a path that optimizes the worst-case performance over an uncertainty set containing all relevant scenarios for a…

math.OC2018

Faster Algorithms for Min-max-min Robustness for Combinatorial Problems with Budgeted Uncertainty

André Chassein, Marc Goerigk, Jannis Kurtz +1

We consider robust combinatorial optimization problems where the decision maker can react to a scenario by choosing from a finite set of solutions. This approach is appropriate…

math.OC2017

On Recoverable and Two-Stage Robust Selection Problems with Budgeted Uncertainty

André Chassein, Marc Goerigk, Adam Kasperski +1

In this paper the problem of selecting out of available items is discussed, such that their total cost is minimized. We assume that costs are not known exactly, but stem fr…

math.OC2016

Variable-Sized Uncertainty and Inverse Problems in Robust Optimization

André Chassein, Marc Goerigk

In robust optimization, the general aim is to find a solution that performs well over a set of possible parameter outcomes, the so-called uncertainty set. In this paper, we assume…

math.OC2016

Min-Max Regret Problems with Ellipsoidal Uncertainty Sets

A. Chassein, M. Goerigk

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 min…