Abstract
People often face the problem of selecting a set of preferred alternatives from a large scale of alternatives, and due to the limited personal cognition, the judgments of decision-makers may distort a rational choice. This study puts forward a two-stage model to solve the decision-making problems with massive alternatives based on the regret theory. In the first stage, a method is proposed to narrow the set of alternatives so as to screen the relative better alternatives from a large number of options. In the second stage, by taking into accounts decision-makers' psychological behavior, a regret-theory-based method is applied to choose the optimal alternative from the narrowed candidate set. In addition, as it is a challenge for decision-makers to make precise evaluations in a highly uncertain decision-making environment, the evaluations in this study are represented by hesitant fuzzy sets to deal with ambiguous and uncertain information. An illustrative example is given to verify the applicability and effectiveness of the proposed model.