Paul Scheidt
University of Marburg
3 Papers
9 Citations
Paul Scheidt is an academic researcher from University of Marburg. The author has contributed to research in topics: Set (abstract data type) & Robust optimization. The author has an hindex of 1, co-authored 3 publications. Previous affiliations of Paul Scheidt include University of Siegen.
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Papers
•Dissertation
Algorithms and Concepts for Robust Optimization
Marc Goerigk,Paul Scheidt +1 more
- 14 Jan 2013
TL;DR: The software library ROPI is presented as a framework for robust optimization with support for most established mixed-integer programming solvers with both theoretical and algorithmic aspects.
Two-Stage robust optimization problems with two-stage uncertainty
TL;DR: In this article , the authors consider two-stage robust optimization problems, where the adversary chooses a scenario from a specified uncertainty set, and the decision maker can react to this scenario by completing the partial first-stage solution to a full solution.
Algorithms and Concepts for Robust Optimization
Paul Scheidt
- 20 Feb 2022
TL;DR: In this paper , the authors introduce the approaches RecFeas and RecOpt to robust optimization problems, using a location theoretic point of view, and discuss both theoretical and algorithmic aspects.