An intelligent approach for the evaluation of innovation projects

Abstract

In this study, an intelligent approach is presented for the evaluation and selection of innovation projects. Selecting the best innovation project is a complicated multiple criteria decision making (MCDM) problem with several potentially competing quantitative and qualitative criteria. In this paper, two hesitant fuzzy MCDM methods; hesitant fuzzy Analytic Hierarchy Process (hesitant F-AHP) and hesitant fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje (hesitant F-VIKOR) are integrated to evaluate and rank innovation projects. In the hesitant fuzzy AHP-VIKOR, hesitant F-AHP is used to find fuzzy evaluation criteria weights and hesitant F-VIKOR is implemented to rank innovation project alternatives. A numerical example is given where five innovation projects are evaluated based on nine criteria by three decision makers.