Dynamic multiple criteria group decision-making method based on intuitionistic fuzzy information

Abstract

In the decision-making process, the decision information provided by decision makers over alternatives may take the form of intuitionistic fuzzy numbers and come from different periods. The weight of information on decision makers, criteria, periods is usually completely unknown. To this issue, we first utilise hesitation degree information and introduce the concept of confidence degree function to determine the decision maker’s weights. Then we aggregate individual evaluation information into group evaluation information through intuitionistic fuzzy number weighted arithmetic averaging operator. We construct a nonlinear optimisation model to gain the criterion weights and apply the aggregate operator to gain the integrated rating value of alternatives in different periods, calculating the deviations of the integrated rating values with respect to their average. Then the period weights are been obtained by using the entropy method. According to the closeness coefficient between alternatives and ideal solution to sort the alternatives and select the optimal one.