Multi-attribute decision making with generalized fuzzy numbers

Abstract

This paper proposes a multi-attribute decision-making method with generalized fuzzy numbers (GFNs). In the proposed method, the distance between GFNs is calculated using the Hausdorff distance. Based on the maximizing deviation degree, the attribute weights are determined by a linear programming model. Furthermore, a ranking formula with a modified possibility degree is adopted to rank alternatives. A numerical example is introduced to validate the proposed model, and the results indicate that the proposed model offers a practical and effective way to meet the different assessment requirements of decision makers.