METHOD OF MULTI-CRITERIA GROUP DECISION-MAKING IN AN EMERGENCY SITUATION USING FUZZY HESITANT SETS
Abstract
In case of an emergency, effective emergency measures must be taken. It is known that an emergency
event has the characteristics of limited time and information, harmfulness and uncertainty, and decision
makers are often limited in rationality in conditions of uncertainty and risk. People's psychological behavior
should be taken into account in real decision-making processes. Decision-making in emergency situations
is an urgent task and the subject of research interests. This article presents a new approach to emergency
decision-making using fuzzy oscillating sets. To determine the weights of the criteria, a mathematical
model is built that allows you to convert the values of the criteria into a compatible scale and exclude
the influence of different scales for their measurements. In order to display the psychological behavior of
decision makers, a function of the degree of group satisfaction and a function of the value of the perceived
usefulness of the alternative are introduced. The usefulness of alternatives is calculated and ranked, and
an example of an emergency study is given. Compared with existing methods, the proposed method for
decision-making in an emergency situation has the following features: the possibilities for determining the
weights of decision-making criteria are expanded when the criteria have a different scale; the method
takes into account the psychology of LPR, unlike well-known approaches that assume the rationality of
LPR decisions; compared with the theory of prospectuses, the method does not require a subjective assessment
of the level of It uses fewer parameters, which expands the scope of its application. The proposed
method also has some limitations: certain computational costs are required with a large number of alternative
solutions and their characteristic attributes. However, this limitation is overcome when using software
such as MATLAB. It is interesting to consider the possibility in the future to apply the proposed
method for risk assessment tasks when making decisions in conditions of fuzzy information, if the attribute
values are random variables.
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