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Eliciting Multi-Criteria Preferences: ELECTRE Models

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Elicitation

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 261))

Abstract

Outranking methods are a specific type of Multi-Criteria Decision Aiding methods. They are based on the construction of binary relations validating or invalidating, for any pair of alternatives (a, b), the assertion “a outranks b”. This comparison is grounded on the evaluation vectors of both alternatives, and on additional information concerning the decision maker’s preferences, typically accounting for two conditions: concordance and non-discordance. In decision processes using these methods, the analyst should interact with the decision maker in order to elicit values for the parameters that define a preference model. This can be done either directly or through a disaggregation procedure that infers parameter values from holistic judgements provided by the decision maker. In this chapter we discuss the elicitation of an outranking-based preference model, focusing on the valued outranking relation used in the ELECTRE III and ELECTRE TRI methods.

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Author information

Authors and Affiliations

  1. Faculty of Economics, CeBER and INESC Coimbra, University of Coimbra, Av. Dias da Silva 165, 3004-512, Coimbra, Portugal

    Luis C. Dias

  2. Laboratoire Génie Industriel, CentraleSupélec, Châtenay-Malabry, France

    Vincent Mousseau

Authors
  1. Luis C. Dias
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  2. Vincent Mousseau
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Correspondence to Luis C. Dias .

Editor information

Editors and Affiliations

  1. Faculty of Economics, CeBER and INESC Coimbra, University of Coimbra, Coimbra, Portugal

    Luis C. Dias

  2. Department of Management Science, University of Strathclyde, Scotland, United Kingdom

    Alec Morton

  3. Department of Management Science, University of Strathclyde, Scotland, United Kingdom

    John Quigley

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Dias, L.C., Mousseau, V. (2018). Eliciting Multi-Criteria Preferences: ELECTRE Models. In: Dias, L., Morton, A., Quigley, J. (eds) Elicitation. International Series in Operations Research & Management Science, vol 261. Springer, Cham. https://doi.org/10.1007/978-3-319-65052-4_14

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