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Preference elicitation for a ranking method based on multiple reference profiles

Author

Listed:
  • Alexandru-Liviu Olteanu

    (Université de Bretagne Sud)

  • Khaled Belahcene

    (Université de Technologie de Compiègne)

  • Vincent Mousseau

    (Université Paris-Saclay)

  • Wassila Ouerdane

    (Université Paris-Saclay)

  • Antoine Rolland

    (Université de Lyon 2)

  • Jun Zheng

    (Université Paris-Saclay)

Abstract

Multiple criteria decision aid methodologies support decision makers (DM) facing decisions involving conflicting objectives. DM’s preferences should be captured to provide meaningful recommendations. Preference elicitation aims at incorporating DM’s preferences in decision models. We propose a new preference elicitation tool for a ranking model based on reference points (RMP—Ranking with Multiple Profiles). Our methodology infers an RMP model from a list of pairwise comparisons provided by the DM. The inference algorithm makes use of a Mixed Integer mathematical programming formulation. We prove the applicability by performing extensive numerical experiments on datasets whose size corresponds to real-world problem.

Suggested Citation

  • Alexandru-Liviu Olteanu & Khaled Belahcene & Vincent Mousseau & Wassila Ouerdane & Antoine Rolland & Jun Zheng, 2022. "Preference elicitation for a ranking method based on multiple reference profiles," 4OR, Springer, vol. 20(1), pages 63-84, March.
    • Handle: RePEc:spr:aqjoor:v:20:y:2022:i:1:d:10.1007_s10288-020-00468-5
    DOI: 10.1007/s10288-020-00468-5
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    References listed on IDEAS

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    Cited by:

    1. Arwa Khannoussi & Alexandru-Liviu Olteanu & Patrick Meyer & Nawal Benabbou, 2024. "A regret-based query selection strategy for the incremental elicitation of the criteria weights in an SRMP model," Operational Research, Springer, vol. 24(2), pages 1-21, June.
    2. Bezoui, Madani & Olteanu, Alexandru-Liviu & Sevaux, Marc, 2023. "Integrating preferences within multiobjective flexible job shop scheduling," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1079-1086.

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