A new optimal consensus method with minimum cost in fuzzy group decision

Juan Liu; Tung Sun Chan; Ya Li; Yajuan Zhang; Yong Deng

doi:10.1016/j.knosys.2012.04.015

A new optimal consensus method with minimum cost in fuzzy group decision

Juan Liu, Tung Sun Chan, Ya Li, Yajuan Zhang, Yong Deng

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

67 Citations (Scopus)

Abstract

Finding group consensus plays a very important role in group decision making (GDM). In this short communication, a new optimal consensus method with minimum cost in fuzzy GDM is proposed. The main contribution of our work is that the limit of each expert's compromise is under consideration in the process of reaching group consensus. The numerical example shows the efficiency of the proposed method.

Original language	English
Pages (from-to)	357-360
Number of pages	4
Journal	Knowledge-Based Systems
Volume	35
DOIs	https://doi.org/10.1016/j.knosys.2012.04.015
Publication status	Published - 1 Nov 2012

Keywords

Fuzzy opinions aggregation
Fuzzy sets
Group decision making
Maximum compromise
Minimum cost consensus

ASJC Scopus subject areas

Software
Management Information Systems
Information Systems and Management
Artificial Intelligence

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10.1016/j.knosys.2012.04.015

Cite this

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abstract = "Finding group consensus plays a very important role in group decision making (GDM). In this short communication, a new optimal consensus method with minimum cost in fuzzy GDM is proposed. The main contribution of our work is that the limit of each expert's compromise is under consideration in the process of reaching group consensus. The numerical example shows the efficiency of the proposed method.",

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AU - Chan, Tung Sun

AU - Li, Ya

AU - Zhang, Yajuan

AU - Deng, Yong

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AB - Finding group consensus plays a very important role in group decision making (GDM). In this short communication, a new optimal consensus method with minimum cost in fuzzy GDM is proposed. The main contribution of our work is that the limit of each expert's compromise is under consideration in the process of reaching group consensus. The numerical example shows the efficiency of the proposed method.

KW - Fuzzy opinions aggregation

KW - Fuzzy sets

KW - Group decision making

KW - Maximum compromise

KW - Minimum cost consensus

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DO - 10.1016/j.knosys.2012.04.015

M3 - Journal article

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VL - 35

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JO - Knowledge-Based Systems

JF - Knowledge-Based Systems

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A new optimal consensus method with minimum cost in fuzzy group decision

Abstract

Keywords

ASJC Scopus subject areas

More information

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