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

Abstract

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

A novel distance measure for probabilistic linguistic term sets with application to emergency decision-making

“…Aiming at the psychological behavior of DMs, Chen et al (2024) based on the regret theory and the multi-attributive border approximation area comparison to reduce the regret of DMs and improve the quality of decision results; The  Zhiying Wang zywang87@163.com 1 School of Management Science and Engineering, Anhui University of Technology, Ma'anshan, Anhui 243032, China prospect theory was applied to EDM by Li et al (2023a) to deal with the bounded rational behavior of DMs. The decision preference of experts was considered and the prospect theory was introduced by Wang and Chen (2023) to obtain the perceived utility of experts. By integrating the emotional adjustment mechanism of DMs, a multistage EDM scheme combined cumulative prospect theory and intuitionistic fuzzy numbers was proposed by .…”

A cloud model-based probabilistic linguistic multi-attribute decision method and its application to public evacuation in nuclear accidents

“…Multi-attribute decision problems have been widely used in recent years Tesfay et al 2023;Chuan et al 2023;Ullah et al 2023;Wang et al 2023;Mehdi et al 2023), but the development of multi-attribute decision problems in a probabilistic linguistic term set environment is not mature enough. Han et al (2023) defined a new distance measure and construct a group consensus method for sequential three-branch decision making based on it.…”