.png){kind=icon}
.png){kind=icon}
Return
A consensus model in multi-attribute large-scale group decision-making based on the relative projection of preference relations with self-confidence
.png){kind=icon}
PRE
AI
Z
J
Y
DOI：10.1007/s10489-026-07347-2.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In multi-attribute large-scale group decision-making (MALSGDM), reaching consensus within the group is key to obtaining a reasonable decision solution. In this study, a dual consensus measurement index based on relative projection is defined from both mathematical and psychological behavioral perspectives: the individual relative projection intra-consensus index (RPICI) and the subgroup relative projection inter-consensus index (RPSICI). A dynamic weight update mechanism is established for experts that reflects the dynamic evolution of experts’ influence and the significance of subgroups during the decision-making process. A two-stage consensus optimization strategy with a dual-weight penalty mechanism is designed to reduce the influence of individuals and subgroups with low consensus, and a compensation mechanism for key expert weights is introduced to effectively reduce the possibility of non-cooperative behavior. An intelligent optimization algorithm is also developed. This optimization algorithm, together with the proposed consensus model, can significantly improve consensus efficiency in complex decision-making environments while enhancing the robustness and rationality of the decision outcomes.
Keywords:
Multiple-attribute large-scale group decision-making
Relative projection
Consensus index
Weight
Journal
IF:
3.5
Papers:
7.5K
Citations:
1.7W
Organization
Cited Papers