Neutrosophic TOPSIS with Group Decision Making

Abstract

Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is an effective tool for multi-attribute decision making. We present a general overview about the development of TOPSIS strategies in neutrosophic environments. In this chapter, we extend TOPSIS strategy to solve multi-attribute group decision making problems in single valued neutrosophic set as well as interval neutrosophic set environments. To develop the proposed TOPSIS strategies, the weights of decision makers are determined by using similarity measure based on Hamming distance. We aggregate each decision maker’s ratings to make common decision using aggregation operators. Employing revised closeness coefficient, we select the best option in the proposed TOPSIS strategies. To demonstrate the applicability and effectiveness of the proposed TOPSIS strategy, we solve two numerical examples of multi-attribute group decision making problems.