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A review of methods for capacity identification in Choquet integral based multi-attribute utility theory: Applications of the Kappalab R package

Author

Listed:
  • Michel Grabisch

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Ivan Kojadinovic

    (LINA - Laboratoire d'Informatique de Nantes Atlantique - Mines Nantes - Mines Nantes - UN UFR ST - Université de Nantes - UFR des Sciences et des Techniques - UN - Université de Nantes - CNRS - Centre National de la Recherche Scientifique)

  • Patrick Meyer

    (Lab-STICC_TB_CID_DECIDE - Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance - UEB - Université européenne de Bretagne - European University of Brittany - ENIB - École Nationale d'Ingénieurs de Brest - UBS - Université de Bretagne Sud - UBO - Université de Brest - Télécom Bretagne - IBNM - Institut Brestois du Numérique et des Mathématiques - UBO - Université de Brest - ENSTA Bretagne - École Nationale Supérieure de Techniques Avancées Bretagne - IMT - Institut Mines-Télécom [Paris] - CNRS - Centre National de la Recherche Scientifique)

Abstract
The application of multi-attribute utility theory whose aggregation process is based on the Choquet integral requires the prior identification of a capacity. The main approaches to capacity identification proposed in the literature are reviewed and their advantages and inconveniences are discussed. All the reviewed methods have been implemented within the Kappalab R package. Their application is illustrated on a detailed example.

Suggested Citation

  • Michel Grabisch & Ivan Kojadinovic & Patrick Meyer, 2008. "A review of methods for capacity identification in Choquet integral based multi-attribute utility theory: Applications of the Kappalab R package," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00187175, HAL.
    • Handle: RePEc:hal:cesptp:halshs-00187175
    DOI: 10.1016/j.ejor.2007.02.025
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00187175
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    1. Denis Bouyssou & Marc Pirlot, 2016. "Conjoint Measurement Tools for MCDM," International Series in Operations Research & Management Science, in: Salvatore Greco & Matthias Ehrgott & José Rui Figueira (ed.), Multiple Criteria Decision Analysis, edition 2, chapter 0, pages 97-151, Springer.
    2. Michel Grabisch & Christophe Labreuche, 2016. "Fuzzy Measures and Integrals in MCDA," International Series in Operations Research & Management Science, in: Salvatore Greco & Matthias Ehrgott & José Rui Figueira (ed.), Multiple Criteria Decision Analysis, edition 2, chapter 0, pages 553-603, Springer.
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    8. Kojadinovic, Ivan, 2007. "Minimum variance capacity identification," European Journal of Operational Research, Elsevier, vol. 177(1), pages 498-514, February.
    9. Grabisch, Michel & Labreuche, Christophe & Vansnick, Jean-Claude, 2003. "On the extension of pseudo-Boolean functions for the aggregation of interacting criteria," European Journal of Operational Research, Elsevier, vol. 148(1), pages 28-47, July.
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