Dynamic Decision Making of Decision-Makers’ Psychological Expectations Based on Interval Triangular Fuzzy Soft Sets

Abstract

Dynamic decision-making is the process of seeking optimal choice with multiple related attributes under the multi-time-point situation. Considering that the time-varying nature of decision information can have a specific impact on the psychology of decision makers, in this paper, a dynamic decision-making method based on the cumulative prospect theory is proposed. Combining this with infinite parameterization of fuzzy soft sets, a time series interval triangular fuzzy soft set is presented, which has characteristics of boundedness, monotonicity, and symmetry. Then, based on the new information priority principle, the exponential decay model is used to determine the time weight coefficient, and a static fuzzy soft matrix is obtained. Furthermore, a method of calculating psychological utility values is proposed, in which the threshold-reference point set is introduced to analyze the psychological “profit and loss” values. Simultaneously, the time probability of the decision-making scenario is transformed into the corresponding weight function. On the basis of prospect maximization theory and maximum entropy theory, an optimization model for determining the weight of decision parameters is established. The cumulative prospect values of the alternatives are given to achieve the best choice for the alternatives. Finally, an example showed the feasibility and effectiveness of this method.