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Evolutionary multi-objective optimization for inferring outranking model’s parameters under scarce reference information and effects of reinforced preference

Evolutionary multi-objective optimization for inferring outranking model’s parameters under... Abstract Methods based on fuzzy outranking relations constitute one of the main approaches to multiple criteria decision problems. The use of ELECTRE methods require the elicitation of a large number of parameters (weights and different thresholds); but direct eliciting is often a demanding task for the decision-maker ( DM ). For handling intensity-ofpreference effects on concordance levels, a generalized concordance model was proposed by Roy and Slowinski which is more complex than previous outranking models. In this paper, an evolutionary multi-objective-based indirect elicitation of the complete ELECTRE III model-parameter set is proposed. The evolutionary multi-objective inference method is successfully extended to inferring reinforced-preference model parameters. Wide experimental evidence is provided to support the proposal, which performs well even working on small size reference sets. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Foundations of Computing and Decision Sciences de Gruyter

Evolutionary multi-objective optimization for inferring outranking model’s parameters under scarce reference information and effects of reinforced preference

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References (23)

Publisher
de Gruyter
Copyright
Copyright © 2012 by the
ISSN
0867-6356
eISSN
0867-6356
DOI
10.2478/v10209-011-0010-0
Publisher site
See Article on Publisher Site

Abstract

Abstract Methods based on fuzzy outranking relations constitute one of the main approaches to multiple criteria decision problems. The use of ELECTRE methods require the elicitation of a large number of parameters (weights and different thresholds); but direct eliciting is often a demanding task for the decision-maker ( DM ). For handling intensity-ofpreference effects on concordance levels, a generalized concordance model was proposed by Roy and Slowinski which is more complex than previous outranking models. In this paper, an evolutionary multi-objective-based indirect elicitation of the complete ELECTRE III model-parameter set is proposed. The evolutionary multi-objective inference method is successfully extended to inferring reinforced-preference model parameters. Wide experimental evidence is provided to support the proposal, which performs well even working on small size reference sets.

Journal

Foundations of Computing and Decision Sciencesde Gruyter

Published: Oct 1, 2012

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