Interval type-2 fuzzy sets extension of analytic hierarchy process with application to new product development project screening

The general interval type-2 fuzzy sets (IT2FS) extension of the analytic hierarchy process (AHP) is developed in this paper. The IT2FS pairwise comparison matrix (PCM) is constructed with IT2FSs as the linguistic judgments given by decision makers. The corresponding extended alpha cut PCMs are formulated. The logarithmic regression functions that are used to elicit the normalized optimal extended alpha cuts of the IT2FS weights are defined and solved. This paper is the first study one that using IT2FS extension of AHP to New Product Development (NPD) project screening problem. Due to the competition accompanied with modern technology and rapid market changes, NPD is highly uncertain. The decision attributes for determining the best NPD project are essentially characterized as possessing not only quantitative but also qualitative. Some critical attributes or criteria are intangible. The design failure for the new product is unavoidable. Implementing the linguistic judgments can greatly enhance the R&D process. A numerical example for NPD project screening criteria is presented for illustrating the proposed methodology.