This paper explores a limited trust propagation-based consensus model considering individual attitude for preference modification in a social networked setting with uncertain preference information. To examine the construction of complete linkages, and the status of decision makers in group decision making, it is assumed that the group size and network density will affect the scale of mediators in the propagation process, then a definition of limited trust propagation is proposed and the propagation efficiency can be introduced. On this basis, we obtain missing trust relationships and individual centrality in network. In the process of consensus reaching, both the decision maker's original preference and recommendation advice are considered for flexibly modeling the preference modification process: the individual attitude toward modification is determined by a newly introduced measure of comprehensive relative out-degree centrality, showing the degree of willingness to adjust assessments. When the willingness is too low to reach the preset consensus level, a multi-objective programming model is designed to improve the consensus as much as possible. Moreover, the proposed feedback mechanism narrows the individual acceptable modification range based on the previous adjustment rule, so as to simulate the personalized and targeted decision behavior. To guarantee obtaining a collective aggregated preference in a logical and precise manner, a two-stage optimization model composing of comprehensive relative in-degree centrality-based information aggregation and best consistency-based uncertainty elimination, is proposed. A numerical example and comparative analyses are performed to show the validity and feasibility of the proposed model.
All Science Journal Classification (ASJC) codes