10 citations · 42 across the 47 of their papers we have counts for
7 papers · 1 filter
On the Complexity of Robust Multi-Stage Problems in the Polynomial Hierarchy
Marc Goerigk, Stefan Lendl, Lasse Wulf
We study the computational complexity of multi-stage robust optimization problems. Such problems are formulated with alternating min/max quantifiers and therefore naturally fall in…
Optimal Scenario Reduction for One- and Two-Stage Robust Optimization
Marc Goerigk, Mohammad Khosravi
Robust optimization typically follows a worst-case perspective, where a single scenario may determine the objective value of a given solution. Accordingly, it is a challenging task…
A Framework for Inherently Interpretable Optimization Models
Marc Goerigk, Michael Hartisch
With dramatic improvements in optimization software, the solution of large-scale problems that seemed intractable decades ago are now a routine task. This puts even more real-world…
A Preference Elicitation Approach for the Ordered Weighted Averaging Criterion using Solution Choice Observations
Werner Baak, Marc Goerigk, Michael Hartisch
Decisions under uncertainty or with multiple objectives usually require the decision maker to formulate a preference regarding risks or trade-offs. If this preference is known, the…
A faster exact method for solving the robust multi-mode resource-constrained project scheduling problem
Matthew Bold, Marc Goerigk
This paper presents a mixed-integer linear programming formulation for the multi-mode resource-constrained project scheduling problem with uncertain activity durations. We consider…
Data-driven Prediction of Relevant Scenarios for Robust Combinatorial Optimization
Marc Goerigk, Jannis Kurtz
We study iterative methods for (two-stage) robust combinatorial optimization problems with discrete uncertainty. We propose a machine-learning-based heuristic to determine starting…
Benchmarking Problems for Robust Discrete Optimization
Marc Goerigk, Mohammad Khosravi
Robust discrete optimization is a highly active field of research where a plenitude of combinations between decision criteria, uncertainty sets and underlying nominal problems are…