Multicriteria decision support using rules that represent rough-graded preference relations

P. Fortemps; Salvatore Greco; R. Slowinski

doi:10.1016/j.ejor.2007.03.036

Multicriteria decision support using rules that represent rough-graded preference relations

P. Fortemps, Salvatore Greco, R. Slowinski

Research output: Contribution to journal › Article › peer-review

Abstract

The approach described in this paper aims to support multicriteria choice and ranking of actions when the input preference information acquired from the decision maker is a graded comprehensive pairwise comparison (or ranking) of reference actions. It is based on decision-rule preference model induced from a rough approximation of the graded comprehensive preference relation among the reference actions. The set of decision rules applied to a new set of actions provides a graded fuzzy preference relation, which can be exploited by weighted-fuzzy net flow score or lexicographic-fuzzy net flow score procedure to obtain a final recommendation in terms of the best choice or of the ranking.

Original language	English
Pages (from-to)	206-223
Number of pages	18
Journal	European Journal of Operational Research
Volume	188
Issue number	1
DOIs	https://doi.org/10.1016/j.ejor.2007.03.036
Publication status	Published - 1 Jul 2008

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abstract = "The approach described in this paper aims to support multicriteria choice and ranking of actions when the input preference information acquired from the decision maker is a graded comprehensive pairwise comparison (or ranking) of reference actions. It is based on decision-rule preference model induced from a rough approximation of the graded comprehensive preference relation among the reference actions. The set of decision rules applied to a new set of actions provides a graded fuzzy preference relation, which can be exploited by weighted-fuzzy net flow score or lexicographic-fuzzy net flow score procedure to obtain a final recommendation in terms of the best choice or of the ranking.",

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Multicriteria decision support using rules that represent rough-graded preference relations

Abstract

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