Development of an interval value fuzzy number based on MCGDM model by hybrid AHP and TOPSIS methods

Abstract

The Purpose research is to develop a new interval value fuzzy by integrating Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for multiple criteria group decision-making model (FMCGDM). The Interval Value Analytic Hierarchy Process (IVFAHP) approach is capable of elaborating complex multi-criteria problems into a hierarchical structure and determining the optimal weight in multi-criteria decision-making. In determining the best alternative, the Interval Value Fuzzy Technique for Order Preference by Similarity to Ideal Solution (IVFTOPSIS) approach is well-suited for being able to make multi-decisions based on the alternative that has the shortest distance from the ideal solution positive and furthest from the ideal negative solution. The results study is a new framework Interval Value Fuzzy (AIVF) decision-making model with flexible linguistic preferences and a high degree of accuracy. The method is implemented in mapping strategy selection problem for measurement e-learning.