Improving Consensus in Group Decision Making with Intuitionistic Reciprocal Preference Relations: A Granular Computing Approach

Abstract

Intuitionistic reciprocal preference relations constitute a flexible and simple representation of decision makers' preference on a set of alternative options, while at the same time allow to accommodate degrees of hesitation inherent to all decision making processes. In this study, we present an approach to support the objective of reaching consensus in group decision making. By using intuitionistic reciprocal preference relations to model the assessments expressed by the decision makers, we propose the concept of a granular intuitionistic reciprocal preference relation in which each pairwise comparison is formed as an interval (information granule) in place of a single numeric value. This provides the flexibility that is required to improve the quality of consensus. With the purpose of illustrating and testing the performance of this approach, an experimental example is provided.