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Ranking robustness and its application to evacuation planning

Author

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  • Goerigk, Marc
  • Hamacher, Horst W.
  • Kinscherff, Anika

Abstract

We present a new approach to handle uncertain combinatorial optimization problems that uses solution ranking procedures to determine the degree of robustness of a solution. Unlike classic concepts for robust optimization, our approach is not purely based on absolute quantitative performance, but also includes qualitative aspects that are of major importance for the decision maker.

Suggested Citation

  • Goerigk, Marc & Hamacher, Horst W. & Kinscherff, Anika, 2018. "Ranking robustness and its application to evacuation planning," European Journal of Operational Research, Elsevier, vol. 264(3), pages 837-846.
    • Handle: RePEc:eee:ejores:v:264:y:2018:i:3:p:837-846
    DOI: 10.1016/j.ejor.2016.05.037
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    References listed on IDEAS

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    1. André Chassein & Marc Goerigk, 2016. "Performance Analysis in Robust Optimization," International Series in Operations Research & Management Science, in: Michael Doumpos & Constantin Zopounidis & Evangelos Grigoroudis (ed.), Robustness Analysis in Decision Aiding, Optimization, and Analytics, chapter 0, pages 145-170, Springer.
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    4. Gorissen, Bram L. & Yanıkoğlu, İhsan & den Hertog, Dick, 2015. "A practical guide to robust optimization," Omega, Elsevier, vol. 53(C), pages 124-137.
    5. Aissi, Hassene & Bazgan, Cristina & Vanderpooten, Daniel, 2009. "Min-max and min-max regret versions of combinatorial optimization problems: A survey," European Journal of Operational Research, Elsevier, vol. 197(2), pages 427-438, September.
    6. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
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