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Lexicographic α-robustness: An alternative to min–max criteria

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  • Kalaı¨, Rim
  • Lamboray, Claude
  • Vanderpooten, Daniel

Abstract

Robustness in Operations Research/Decision Aid is often associated with min–max and min–max regret criteria. This common approach to determine robust solutions consists in finding a solution which minimizes the maximal cost or regret. Nevertheless, these criteria are known to be too conservative. In this paper, we present and study a new robustness approach, called lexicographic α-robustness, which compensates for this major drawback and many others. Furthermore, we establish a link between lexicographic α-robustness and a third robustness approach called p-robustness.

Suggested Citation

  • Kalaı¨, Rim & Lamboray, Claude & Vanderpooten, Daniel, 2012. "Lexicographic α-robustness: An alternative to min–max criteria," European Journal of Operational Research, Elsevier, vol. 220(3), pages 722-728.
    • Handle: RePEc:eee:ejores:v:220:y:2012:i:3:p:722-728
    DOI: 10.1016/j.ejor.2012.01.056
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    Cited by:

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    2. Sandra Cruz Caçador & Pedro Manuel Cortesão Godinho & Joana Maria Pina Cabral Matos Dias, 2022. "A minimax regret portfolio model based on the investor’s utility loss," Operational Research, Springer, vol. 22(1), pages 449-484, March.
    3. Sandra Caçador & Joana Matos Dias & Pedro Godinho, 2020. "Global minimum variance portfolios under uncertainty: a robust optimization approach," Journal of Global Optimization, Springer, vol. 76(2), pages 267-293, February.
    4. Durbach, Ian N., 2014. "Outranking under uncertainty using scenarios," European Journal of Operational Research, Elsevier, vol. 232(1), pages 98-108.

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