A Large Group Emergency Decision Making Method Considering Scenarios and Unknown Attribute Weights

Once an emergency event (EE) happens, decision-making (EDM) plays a key role in mitigating the loss. EDM is complex problem. Compared with conventional problems, more experts participate decision-making. It usually has feature of large group (LGEDM). This paper proposes method based on Bayesian theory, relative entropy, and Euclidean distance, which used for uncertain probabilities occurrence, unknown attribute weights, expert weights. In order to improve accuracy decision-making, introduced into calculation scenario probability process LGEDM. process, experts’ risk preference considered. The decision information symmetric uniformly distributed interval value. perceived utility values are obtained by introducing prospect theory. distance measure contributions aggregation similarity, different weights given according their contributions. A entropy model completely weight constraints established obtain takes account differences alternatives under same between ideal solution. An example nuclear power illustrates effectiveness this method.