D-CFPR: D numbers extended consistent fuzzy preference relations

Xinyang Deng; Xi Lu; Felix T.S. 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, Felix T.S. Chan, Rehan Sadiq, Sankaran Mahadevan, Yong Deng

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

58 Scopus citations

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
State	Published - 1 Jan 2015
Externally published	Yes

Keywords

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

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10.1016/j.knosys.2014.09.007

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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 - Deng, Xinyang

AU - Lu, Xi

AU - Chan, Felix T.S.

AU - Sadiq, Rehan

AU - Mahadevan, Sankaran

AU - Deng, Yong

PY - 2015/1/1

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KW - D numbers

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D-CFPR: D numbers extended consistent fuzzy preference relations

Abstract

Keywords

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