Consensus: The Minimum Cost Model based Robust Optimization

摘要

In decision making, there are opinion conflict for the people involved it. In order to eliminate the opinion conflict, the minimum cost consensus model is proposed to coordinate the opinion of experts. However, in the exiting minimum cost model, the unit adjustment cost of experts is supposed to be fixed. It is hard to get and can be uncertain. Therefore, the purpose of this paper is to propose a consensus model based on robust optimization. In the presented model, it mainly solves the worst-case consensus problem. Subsequently, the detailed consensus feedback adjustment is presented involving two aspects: construct robust counterpart of worst-case consensus and estimate the unit adjustment cost of expert. Finally, through numerical example and comparative analysis, the validity and superiority of the presented consensus model are verified.