D-CFPR: D numbers extended consistent fuzzy preference relations

Xinyang Deng; Xi Lu; Tung Sun Chan; Rehan Sadiq; Sankaran Mahadevan; Yong Deng

doi:10.1016/j.knosys.2014.09.007

D-CFPR: D numbers extended consistent fuzzy preference relations

Xinyang Deng, Xi Lu, Tung Sun Chan, Rehan Sadiq, Sankaran Mahadevan, Yong Deng

Research output: Journal article publication › Journal article › Academic research › peer-review

55 Citations (Scopus)

Abstract

How to express an expert's or decision maker's preference for alternatives is an open issue. Consistent fuzzy preference relation (CFPR) is with big advantages to handle this problem due to it can be construed via a smaller number of pairwise comparisons and satisfies transitivity property. However, the CFPR is incapable of dealing with the cases involving uncertain and incomplete information. In this paper, a D numbers extended consistent fuzzy preference relation (D-CFPR) is proposed to overcome the weakness. The D-CFPR extends the classical CFPR by using a new model of expressing uncertain information called D numbers. The D-CFPR inherits the merits of classical CFPR and can totally reduce to the classical CFPR. This study can be integrated into our previous study about D-AHP (D numbers extended AHP) model to provide a systematic solution for multi-criteria decision making (MCDM).

Original language	English
Pages (from-to)	61-68
Number of pages	8
Journal	Knowledge-Based Systems
Volume	73
DOIs	https://doi.org/10.1016/j.knosys.2014.09.007
Publication status	Published - 1 Jan 2015

Keywords

Belief function
Consistent fuzzy preference relations
D numbers
D-CFPR
Dempster-Shafer evidence theory

ASJC Scopus subject areas

Management Information Systems
Software
Information Systems and Management
Artificial Intelligence

More information

10.1016/j.knosys.2014.09.007

Cite this

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abstract = "How to express an expert's or decision maker's preference for alternatives is an open issue. Consistent fuzzy preference relation (CFPR) is with big advantages to handle this problem due to it can be construed via a smaller number of pairwise comparisons and satisfies transitivity property. However, the CFPR is incapable of dealing with the cases involving uncertain and incomplete information. In this paper, a D numbers extended consistent fuzzy preference relation (D-CFPR) is proposed to overcome the weakness. The D-CFPR extends the classical CFPR by using a new model of expressing uncertain information called D numbers. The D-CFPR inherits the merits of classical CFPR and can totally reduce to the classical CFPR. This study can be integrated into our previous study about D-AHP (D numbers extended AHP) model to provide a systematic solution for multi-criteria decision making (MCDM).",

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AU - Lu, Xi

AU - Chan, Tung Sun

AU - Sadiq, Rehan

AU - Mahadevan, Sankaran

AU - Deng, Yong

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D-CFPR: D numbers extended consistent fuzzy preference relations

Abstract

Keywords

ASJC Scopus subject areas

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