The multi-criteria group decision making methodology using type 2 fuzzy linguistic judgments

Abstract

This paper develops an integrated methodology for multiple criteria and multiple experts decision making problems using type 2 fuzzy sets (T2FS) as the linguistic judgments. The experts or decision maker's opinions are in linguistics forms. The proposed approach is the extension of the analytic hierarchy process (AHP) method for multiple experts. The pairwise or relative comparisons of decision linguistic judgments are characterized by interval type 2 fuzzy sets (IT2FS). The integrated methodology consists of the following stages: 1. Construct IT2FS pairwise comparison matrix (PCM), 2. Elicit IT2FS weights and rates, 3. Normalize the IT2FS weights and rates, 4. Synthesize the IT2FS weights and rates, 5. Calculate the global IT2FS rates, 6. Determine the final decision priority. At the outset of the decision making the IT2FS PCM for a set of criteria is created. The quadratic programming models are constructed to elicit the absolute IT2FS weights of the criteria in the sense of minimizing the least squares logarithmic regression functions. A normalization procedure is introduced for the IT2FS vector to obtain the well-defined and normalized IT2FS weights. Two approaches, the linear programming model and the IT2 fuzzy weighted average (FWA), are developed to synthesize and aggregate the local rates and weights. Thus, the overall global IT2FS rates for the alternatives are obtained. The final decision then can be concluded by the priority of the overall IT2FS rates of the alternatives. The proposed approach is applied to New Product Development (NPD) project screening. NPD is largely uncertain, because of competition accompanied with modern technology and market changes. It always leads to failure of New Product Development. The final project screening decision is obtained from the overall global IT2FS rates of the projects with respect to the screening criteria.