A unified approach for different concepts of robustness and stochastic programming via non-linear scalarizing functionals

By Kathrin Klamroth, Elisabeth Köbis, Anita Schöbel, Christiane Tammer. 2013

64 citations recorded by the source corpus.

Abstract We show that many different concepts of robustness and of stochastic programming can be described as special cases of a general non-linear scalarization method by choosing the involved parameters and sets appropriately. This leads to a unifying concept which can be used to handle robust and stochastic optimization problems. Furthermore, we introduce multiple objective (deterministic) counterparts for uncertain optimization problems and discuss their relations to well-known scalar robust optimization problems by using the non-linear scalarization concept. Finally, we mention some relations between robustness and coherent risk measures.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/817c2aef0670b88827e091acdb641e340cbfb6b8

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In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

On Robust Optimization (2015, background): “Köbis and Tammer [10] showed that solutions of the strictly robust OP are at least weakly Pareto optimal for (RC u ).”