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Using the R* Criterion to Selected Optimization Problems Under Uncertainty

Author

Listed:
  • Romain Guillaume

    (Université de Toulouse-IRIT)

  • Adam Kasperski

    (Wrocław University of Science and Technology)

  • Szymon Wróbel

    (Wrocław University of Science and Technology)

  • Paweł Zieliński

    (Wrocław University of Science and Technology)

Abstract

In robust optimization, the impact of uncertainty is typically modeled using the min-max approach, where the goal is to optimize the solution cost under a worst-case scenario. This approach does not take into account good scenarios that can occur and may lead to very conservative solutions. The R* uninorm is an aggregation operator that selects the minimal value when all arguments are below a selected threshold and the maximal value otherwise. Its axiomatic characterization, applications to decision-making, and comparison to the traditional Hurwicz criterion were described by Fargier and Guillaume in 2020. The goal of this paper is to present an application of the R* approach to selected optimization problems under uncertainty.

Suggested Citation

  • Romain Guillaume & Adam Kasperski & Szymon Wróbel & Paweł Zieliński, 2025. "Using the R* Criterion to Selected Optimization Problems Under Uncertainty," Lecture Notes in Operations Research,, Springer.
    • Handle: RePEc:spr:lnopch:978-3-031-92575-7_54
    DOI: 10.1007/978-3-031-92575-7_54
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