Decision-makers (DMs) will face severe challenges when selecting an optimal alternative for an emergency response over multiple time periods. The aim of this paper is to develop a novel dynamic emergency decision-making method with probabilistic hesitant fuzzy information for handling emergencies. First, an approach based on the GM(1,1) model for predicting the decision-making information at the next stage is proposed. Second, a new probabilistic hesitant fuzzy distance measure based on the hesitant degree of the probabilistic hesitant fuzzy element is put forward, and a mathematical programming model to determine the stage weights is established. What is more, the closeness degree between each alternative and the ideal alternative is calculated, and the emergency alternatives are ranked on the strength of the technique for order preference by similarity to an ideal solution method. Moreover, a practical example is used to verify the feasibility and rationality of the proposed method.
INDEX TERMSDynamic emergency decision-making, probabilistic hesitant fuzzy set (PHFS), GM(1,1) model, TOPSIS method. degree in pure mathematics from Wuhan University, and management science from College of Economics and Management at Nanjing University of Aeronautics and Astronautics, China, respectively. He is an Associate Professor in the school of mathematics and Physics at Anhui University of Technology. His research areas are multiple attribute decision making, clustering analysis, and aggregation operators. His articles are published in the Technological and Economic
Once an emergency event occurs, effective emergency measures should be taken. It is known that the emergency event possesses characteristics of limited time and information, harmfulness, and uncertainty, and the decision makers are often bounded rational under uncertainty and risk. This paper presents a novel approach to emergency decision making with hesitant fuzzy information, which takes regret aversion of the decision makers into account. Firstly, based on the idea of the water-filling theory in the field of wireless communications, a mathematical programming model that can convert the attribute values into a compatible scale and eliminate the influence of different physical dimensions is constructed to determine the attribute weights. Then, a group satisfaction degree function is introduced into the regret theory to depict the psychological behaviors of the decision makers, based on which the perceived utility value function of alternative is constructed. The total perceived utility values of alternatives can be computed, and the ranking order of alternatives is obtained. Finally, a case study on a fire and explosion accident is given to illustrate the application of the proposed method. Besides that, the comparisons show the feasibility and superiority of the proposed method.
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