The robust minimum cost consensus model with risk aversion

Due to the uncertain circumstances in which decisions are made, the moderator may be unable to provide an accurate unit adjustment cost to each decision maker, making the unit adjustment cost uncertain. This paper formulates a consensus approach to reduce the adverse effects of parameter uncertainty and estimation errors. First, the mean–variance (MV) theory is employed to build the risk minimum cost consensus model (RMCCM) to reflect the risk preference of the moderator in the consensus progress. Second, due to existing estimation errors of the mean and covariance matrix of unit adjustment cost in RMCCM, new RMCCM variants are proposed using robust optimization. To identify a solution that performs best in the worst case, the robust counterpart RMCCM problem is equivalent to a tractable problem. Finally, a case study of urban housing demolition in China is used to verify the feasibility and applicability of the proposed method, and then sensitivity analysis and comparative analysis are presented.