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Incomplete Fuzzy Preference Relations and their Fusion

Authors: Tien-chin Wang; Ying-ling Lin;

Incomplete Fuzzy Preference Relations and their Fusion

Abstract

Because of decision makers having limited attention spans and information processing capabilities, as well as some decision alternatives being incomparable, decision makers may develop incomplete preference relations in which some elements cannot be provided. The method proposed by Herrera et al. devises a consistent preference relation that is restricted by the set of n ? 1 values {p12, p23,..., pn?1n}. Therefore, for convenience and flexibility, the following uses the incomplete fuzzy preference relation with the least judgments (that is, n ? 1 judgments) to develop a simple and practical method for constructing a consistent complete fuzzy preference relation in which experts can compare any row, column or diagonal. The proposed method is more convenient and flexible than that of Herrera et al.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
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