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Preference Representation by Means of Conjoint Measurement and Decision Rule Model

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Aiding Decisions with Multiple Criteria

Abstract

We investigate the equivalence of preference representation by numerical functions and by “if ..., then...” decision rules in multicriteria choice and ranking problems. The numerical function is a general non-additive and non-transitive model of conjoint measurement. The decision rules concern pairs of actions and conclude either presence or absence of a comprehensive preference relation; conditions for the presence are expressed in “at least” terms, and for the absence in “at most” terms, on particular criteria. Moreover, we consider representation of hesitation in preference modeling. Within this context, two approaches are considered: dominance-based rough set approach—handling inconsistencies in expression of preferences through examples, and four-valued logic—modeling the presence of positive and negative reasons for preference. Equivalent representation by numerical functions and by decision rules is proposed and a specific axiomatic foundation is given for preference structure based on the presence of positive and negative reasons. Finally, the following well known multicriteria aggregation procedures are represented in terms of the decision rule model: lexicographic aggregation, majority aggregation, ELECTRE I and TACTIC.

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Denis Bouyssou Eric Jacquet-Lagrèze Patrice Perny Roman Słowiński Daniel Vanderpooten Philippe Vincke

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Greco, S., Matarazzo, B., Słowiński, R. (2002). Preference Representation by Means of Conjoint Measurement and Decision Rule Model. In: Bouyssou, D., Jacquet-Lagrèze, E., Perny, P., Słowiński, R., Vanderpooten, D., Vincke, P. (eds) Aiding Decisions with Multiple Criteria. International Series in Operations Research & Management Science, vol 44. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0843-4_13

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  • DOI: https://doi.org/10.1007/978-1-4615-0843-4_13

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-5266-2

  • Online ISBN: 978-1-4615-0843-4

  • eBook Packages: Springer Book Archive

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