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CUT: A Multicriteria Approach for Concavifiable Preferences

Author

Listed:
  • Nikolaos Argyris

    (Department of Statistics, University of Warwick, Coventry CV4 7AL, United Kingdom)

  • Alec Morton

    (Department of Management Science, Strathclyde Business School, Glasgow G1 1XQ, United Kingdom)

  • José Rui Figueira

    (CEG-IST, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal)

Abstract

We consider the problem of helping a decision maker (DM) choose from a set of multiattributed objects when her preferences are “concavifiable,” i.e. representable by a concave value function. We establish conditions under which preferences or preference intensities are concavifiable. We also derive a characterization for the family of concave value functions compatible with a set of such preference statements expressed by the DM. This can be used to validate dominance relations over discrete sets of alternatives and forms the basis of an interactive procedure. We report on the practical use of this procedure with several DMs for a flat-choice problem and its computational performance on a set of project-portfolio selection problem instances. The use of preference intensities is found to provide significant improvements to the performance of the procedure.

Suggested Citation

  • Nikolaos Argyris & Alec Morton & José Rui Figueira, 2014. "CUT: A Multicriteria Approach for Concavifiable Preferences," Operations Research, INFORMS, vol. 62(3), pages 633-642, June.
    • Handle: RePEc:inm:oropre:v:62:y:2014:i:3:p:633-642
    DOI: 10.1287/opre.2014.1274
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    References listed on IDEAS

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    Cited by:

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    2. Simon French & Nikolaos Argyris, 2018. "Decision Analysis and Political Processes," Decision Analysis, INFORMS, vol. 15(4), pages 208-222, December.
    3. Peter Reichert & Klemens Niederberger & Peter Rey & Urs Helg & Susanne Haertel-Borer, 2019. "The need for unconventional value aggregation techniques: experiences from eliciting stakeholder preferences in environmental management," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 7(3), pages 197-219, November.
    4. Selin Özpeynirci & Özgür Özpeynirci & Vincent Mousseau, 2021. "An interactive algorithm for resource allocation with balance concerns," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 983-1005, December.
    5. Vilkkumaa, Eeva & Liesiö, Juuso & Salo, Ahti & Ilmola-Sheppard, Leena, 2018. "Scenario-based portfolio model for building robust and proactive strategies," European Journal of Operational Research, Elsevier, vol. 266(1), pages 205-220.
    6. Karsu, Özlem & Morton, Alec & Argyris, Nikos, 2018. "Capturing preferences for inequality aversion in decision support," European Journal of Operational Research, Elsevier, vol. 264(2), pages 686-706.
    7. Cinelli, Marco & Kadziński, Miłosz & Miebs, Grzegorz & Gonzalez, Michael & Słowiński, Roman, 2022. "Recommending multiple criteria decision analysis methods with a new taxonomy-based decision support system," European Journal of Operational Research, Elsevier, vol. 302(2), pages 633-651.
    8. Argyris, Nikolaos & French, Simon, 2017. "Nuclear emergency decision support: A behavioural OR perspective," European Journal of Operational Research, Elsevier, vol. 262(1), pages 180-193.
    9. Argyris, Nikolaos & Østerdal, Lars Peter & Hussain, M. Azhar, 2023. "Value-driven Multidimensional Welfare Analysis: A Dominance Approach with Application to Comparisons of European Populations," Working Papers 12-2023, Copenhagen Business School, Department of Economics.
    10. Liesiö, Juuso & Salo, Ahti & Keisler, Jeffrey M. & Morton, Alec, 2021. "Portfolio decision analysis: Recent developments and future prospects," European Journal of Operational Research, Elsevier, vol. 293(3), pages 811-825.

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