A unified approach to uncertain optimization
Klamroth K, Koebis E, Schoebel A, Tammer C (2017)
Publication Type: Journal article
Publication year: 2017
Journal
Book Volume: 260
Pages Range: 403-420
Journal Issue: 2
DOI: 10.1016/j.ejor.2016.12.045
Abstract
In this paper we consider uncertain scalar optimization problems with infinite scenario sets. We apply methods from vector optimization in general spaces, set-valued optimization and scalarization techniques to develop a unified characterization of different concepts of robust optimization and stochastic programming. These methods provide new insights on the interrelation between different concepts for handling uncertainties and naturally lead to new concepts of robustness.
Involved external institutions
Bergische Universität Wuppertal
Germany (DE)
Martin-Luther-Universität Halle-Wittenberg (MLU)
Germany (DE)
Georg-August-Universität Göttingen
Germany (DE)
Germany (DE)
Martin-Luther-Universität Halle-Wittenberg (MLU)
Germany (DE)
Georg-August-Universität Göttingen
Germany (DE)
How to cite
APA:
Klamroth, K., Koebis, E., Schoebel, A., & Tammer, C. (2017). A unified approach to uncertain optimization. European Journal of Operational Research, 260(2), 403-420. https://doi.org/10.1016/j.ejor.2016.12.045
MLA:
Klamroth, Kathrin, et al. "A unified approach to uncertain optimization." European Journal of Operational Research 260.2 (2017): 403-420.
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