Paper Info
Title
The classification-based consensus in multi-attribute group decision-making
Abstract
In multi-attribute group decision-making problem (MAGDM), the existing consensus reaching process (CRP) is to obtain a consensus ranking of alternatives. However, these CRPs contradict some real-life MAGDM problems in which decision-makers do not need to rank alternatives and hope to classify the alternatives into several groups instead. Thus, in this paper we propose a new CRP in MAGDM, called the classification-based consensus reaching process (CCRP). First, we present a feedback method with minimum adjustments to generate the optimal adjusted individual matrices via a 0-1 mixed linear programming model for CCRP. Subsequently, we develop the interactive consensus reaching process based on the feedback method with minimum adjustments in CCRP. Finally, a practical example from China Undergraduate Mathematical Contest in Modeling and a simulation analysis are conducted to demonstrate the validity of the proposed CCRP.
Year
DOI
Venue
2020
10.1080/01605682.2019.1609888
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
Keywords
DocType
Volume
Multi-attribute group decision-making,consensus,feedback method,minimum adjustments,classification
Journal
71.0
Issue
ISSN
Citations 
9.0
0160-5682
2
PageRank 
References 
Authors
0.35
0
4
Name
Order
Citations
PageRank
Chen Xin1625120.92
Wei-Jun Xu215414.56
Haiming Liang312214.63
Yucheng Dong4283199.15