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Simple ranking method using reference profiles: incremental elicitation of the preference parameters

Author

Listed:
  • Arwa Khannoussi

    (Université Lumière Lyon 2)

  • Alexandru-Liviu Olteanu

    (Université Bretagne Sud)

  • Christophe Labreuche

    (Thales Group)

  • Patrick Meyer

    (IMT Atlantique)

Abstract

The Simple Ranking Method using Reference Profiles (or SRMP) is a Multi-Criteria Decision Aiding technique based on the outranking paradigm, which allows to rank decision alternatives according to the preferences of a decision maker (DM). Inferring the preference parameters of such a model can lead to a cognitive fatigue of the DM, who is often asked to express several preferential statements about pairs of alternatives during the elicitation process. To limit the DM’s effort, we propose in this work an incremental elicitation process to select informative pairs of alternatives to be presented to the DM sequentially with the aim of refining the SRMP model until a robust recommendation can be made. We study several different heuristics for selecting the pair of alternatives to be submitted to the DM at each step. Following extensive numerical experiments we identify one of the proposed heuristics as performing significantly better than the others and we provide several guidelines for its use in practice.

Suggested Citation

  • Arwa Khannoussi & Alexandru-Liviu Olteanu & Christophe Labreuche & Patrick Meyer, 2022. "Simple ranking method using reference profiles: incremental elicitation of the preference parameters," 4OR, Springer, vol. 20(3), pages 499-530, September.
    • Handle: RePEc:spr:aqjoor:v:20:y:2022:i:3:d:10.1007_s10288-021-00487-w
    DOI: 10.1007/s10288-021-00487-w
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    References listed on IDEAS

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    1. Greco, Salvatore & Matarazzo, Benedetto & Slowinski, Roman, 2001. "Rough sets theory for multicriteria decision analysis," European Journal of Operational Research, Elsevier, vol. 129(1), pages 1-47, February.
    2. Rolland, Antoine, 2013. "Reference-based preferences aggregation procedures in multi-criteria decision making," European Journal of Operational Research, Elsevier, vol. 225(3), pages 479-486.
    3. Bouyssou, Denis & Marchant, Thierry, 2013. "Multiattribute preference models with reference points," European Journal of Operational Research, Elsevier, vol. 229(2), pages 470-481.
    4. Mousseau, Vincent & Figueira, Jose & Dias, Luis & Gomes da Silva, Carlos & Climaco, Joao, 2003. "Resolving inconsistencies among constraints on the parameters of an MCDA model," European Journal of Operational Research, Elsevier, vol. 147(1), pages 72-93, May.
    5. Bouyssou, Denis & Pirlot, Marc, 2009. "An axiomatic analysis of concordance-discordance relations," European Journal of Operational Research, Elsevier, vol. 199(2), pages 468-477, December.
    6. Ciomek, Krzysztof & Kadziński, Miłosz & Tervonen, Tommi, 2017. "Heuristics for selecting pair-wise elicitation questions in multiple criteria choice problems," European Journal of Operational Research, Elsevier, vol. 262(2), pages 693-707.
    7. Holloway, Hillary A. & White III, Chelsea C., 2003. "Question selection for multi-attribute decision-aiding," European Journal of Operational Research, Elsevier, vol. 148(3), pages 525-533, August.
    8. Butler, John & Jia, Jianmin & Dyer, James, 1997. "Simulation techniques for the sensitivity analysis of multi-criteria decision models," European Journal of Operational Research, Elsevier, vol. 103(3), pages 531-546, December.
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