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A Relative Projection-Based Multiattribute Group Decision-Making Model With Noncooperative Behavior Management and Application to NEV Supplier Selection.
- Source :
-
IEEE transactions on cybernetics [IEEE Trans Cybern] 2024 Aug 06; Vol. PP. Date of Electronic Publication: 2024 Aug 06. - Publication Year :
- 2024
- Publisher :
- Ahead of Print
-
Abstract
- This article reports a novel consensus model where a group of internal and external experts evaluate alternatives under multiple attributes and provide mutual evaluations. First, different from previous studies, the cognitive and interest conflicts of internal and external experts are considered simultaneously. But interest conflict is emphasized for internal experts, and cognitive conflict is mainly considered for external experts. Second, we explore the categorization and management methods of noncooperative behaviors (NCBs) of experts. The relative projection-based indexes are proposed for the first time to measure the degrees of cognitive and interest conflicts by using multiattribute preference matrices (MAPMs) and the weight vectors of attributes. A group of experts are divided into three categories and the corresponding management strategies are developed. Third, we investigate the consensus mechanism among experts with cognitive and interest conflicts. For reaching an acceptable consensus level, an adjustment process is proposed to revise some local entries in MAPMs and mutual evaluation matrix (MEM). A penalty mechanism is further established to dynamically update the weights of experts. An algorithm is designed to capture the consensus reaching process in multiattribute group decision making, where internal and external experts are distinguished by proposing a parameter. Finally, the high-performance battery supplier selection of new energy vehicle is studied to illustrate the proposed model. The results reveal that the efficiency of reaching consensus can be enhanced by using the developed model with effective management of NCBs.
Details
- Language :
- English
- ISSN :
- 2168-2275
- Volume :
- PP
- Database :
- MEDLINE
- Journal :
- IEEE transactions on cybernetics
- Publication Type :
- Academic Journal
- Accession number :
- 39106133
- Full Text :
- https://doi.org/10.1109/TCYB.2024.3430243