A Fuzzy Interpolation Method to Group Decision Making using Interval Type-2 Fuzzy Sets

The goal in group decision making is to ensure that the best decision is made in terms of the available information and knowledge possessed by all group members. However, different types of uncertainty may influence both the assessment of the individual views and the derivation of the overall group-based solution. The difficulty in such decision making process may escalate if the views of all individuals only cover part of the problem space. Systems capable of reasoning through fuzzy interpolation can help. Fuzzy rule interpolation is an important technique for performing inference in sparse rule bases. Even when a given observation has no overlap with the antecedent values of any existing rules, fuzzy rule interpolation may still derive a certain conclusion. This paper proposes a method for achieving group decision making via interval type-2 fuzzy interpolation. Individual preferences are firstly aggregated by means of interval type-2 fuzzy sets, and interval type-2 fuzzy interpolation is then applied to derive the group-based conclusion. Experimental investigations are carried out and comparative results are presented to demonstrate the efficacy of the proposed work in guaranteeing the overall decision accuracy.