The classification-based consensus in multi-attribute group decision-making. Issue 9 (1st September 2020)

• Record Type: Journal Article
• Authors: Chen, Xin; Xu, Weijun; Liang, Haiming; Dong, Yucheng
• Is Part Of: Journal of the Operational Research Society. Volume 71:Issue 9(2020)
• Page Start: 1375
• Page End: 1389
• Publication Date: 2020-09-01
• Subjects: Multi-attribute group decision-making -- consensus -- feedback method -- minimum adjustments -- classification; Operations research -- Periodicals; 658.4034
• DOI: 10.1080/01605682.2019.1609888
• Languages: English
• ISSNs: 0160-5682

Abstract

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.