Group Decision Analysis Algorithms with EDAS for Interval Fuzzy Sets

The purpose of this paper is proposing, analyzing and assessing two new algorithms of the EDAS method for group multi-criteria decision making with fuzzy sets. In the first proposed EDAS extension for distance measure between two interval Type-2 fuzzy numbers is applied Graded Mean Integration Representation (GMIR). The second algorithm takes into account the proximity between the fuzzy alternatives and its similarity measure is Map Distance Operator (MDO). The two new algorithms are verified by a numerical example. Comparative analysis of obtained rankings demonstrates that GMIR extension is more reliable as an interval Type-2 fuzzy alternative to Evaluation based on Distance from Average Solution (EDAS). In case that time is of the essence, the MDO EDAS could be preferred.