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Inverse multiple criteria sorting problem

Author

Listed:
  • Vincent Mousseau

    (CentraleSupélec, Université Paris Saclay)

  • Özgür Özpeynirci

    (İzmir University of Economics)

  • Selin Özpeynirci

    (İzmir University of Economics)

Abstract

Multiple criteria sorting problem is to assign objects evaluated with multiple criteria to one of the predefined ordered classes. In this study, we consider the inverse multiple criteria sorting problem (IMCSP), in which it is possible to perform actions which have an impact of objects evaluations, hence on the objects classification. IMCSP aims at determining which action(s) to implement so as to provide guaranties on objects classification. Each action has a corresponding cost and impact on the evaluations of objects on each criterion. In this paper we study IMCSP for three different sorting methods: linear, UTADIS and MR-Sort. We consider two levels of information; (i) the sorting method parameters are known explicitly (simple version), and (ii) assignment examples restrict the set of compatible parameters (robust version). We study two types of problems; first, finding the least costly set of actions that guarantees the objects assignment to desired classes, and second, improving the assignment of objects under a limited budget. For each case, we develop a resolution method based on mathematical programming models. Extensive computational experiments on randomly generated instances show the performance and applicability of the approach.

Suggested Citation

  • Vincent Mousseau & Özgür Özpeynirci & Selin Özpeynirci, 2018. "Inverse multiple criteria sorting problem," Annals of Operations Research, Springer, vol. 267(1), pages 379-412, August.
    • Handle: RePEc:spr:annopr:v:267:y:2018:i:1:d:10.1007_s10479-017-2420-8
    DOI: 10.1007/s10479-017-2420-8
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    References listed on IDEAS

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    Cited by:

    1. Khaled Belahcène & Vincent Mousseau & Wassila Ouerdane & Marc Pirlot & Olivier Sobrie, 2023. "Multiple criteria sorting models and methods. Part II: theoretical results and general issues," 4OR, Springer, vol. 21(2), pages 181-204, June.
    2. T. R. Wang & N. Pedroni & E. Zio & V. Mousseau, 2020. "Identification of Protective Actions to Reduce the Vulnerability of Safety‐Critical Systems to Malevolent Intentional Acts: An Optimization‐Based Decision‐Making Approach," Risk Analysis, John Wiley & Sons, vol. 40(3), pages 565-587, March.
    3. Ali Tlili & Oumaima Khaled & Vincent Mousseau & Wassila Ouerdane, 2023. "Interactive portfolio selection involving multicriteria sorting models," Annals of Operations Research, Springer, vol. 325(2), pages 1169-1195, June.
    4. Jindong Qin & Yingying Liang & Luis Martinez & Alessio Ishizaka & Witold Pedrycz, 2023. "ORESTE-SORT: a novel multiple criteria sorting method for sorting port group competitiveness," Annals of Operations Research, Springer, vol. 325(2), pages 875-909, June.
    5. Özgür Özpeynirci & Selin Özpeynirci & Vincent Mousseau, 2023. "A decomposition based minimax regret approach for inverse multiple criteria sorting problem," 4OR, Springer, vol. 21(1), pages 125-149, March.

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