Extended TOPSIS for Group Decision Making with Linguistic Quantifiers and Concept of Majority Opinion

This paper presents a fuzzy extension of TOPSIS (technique for order performance by similarity to ideal solution) with a new quantifier guided distance metric and majority opinion aggregator for multi-criteria decision making in a group decision environment. The proposed distance metric is based on OWA aggregators and provides an opportunity to use linguistic quantifiers to have linguistic definitions for proximity. On the other hand, the majority opinion aggregator is used to make a consensual judgment for synthesizing the individual opinions. A human resource selection problem is considered as the case study, and the proposed algorithm is employed to solve that. Simulation results show that our algorithm is more advantageous in reflecting opinions of the majority of decision makers and providing more confidence for their decisions. Keywords—Multi-Criteria Decision Making, Group Decision Making, TOPSIS, OWA, Majority Opinion.