A fuzzy weighted influence non-linear gauge system with application to advanced technology assessment at NASA. (15th November 2021)

• Record Type: Journal Article
• Authors: Tavana, Madjid; Mousavi, Hossein; Khalili Nasr, Arash; Mina, Hassan
• Is Part Of: Expert systems with applications. Volume 182(2021)
• Publication Date: 2021-11-15
• Subjects: Multi-criteria decision making -- Weighted influence non-linear gauge system -- Fuzzy sets -- Causal maps -- Technology assessment -- NASA; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2021.115274
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: We propose a new fuzzy Weighted Influence Non-linear Gauge System (WINGS). We uncover interdependencies by the direction, intensity and strength of dependencies. Fuzzy judgments are used to cope with uncertainties in untested new technologies. We introduce ideal and nadir alternatives in WINGS to study the solution space. We present a case study to evaluate ten advanced technology projects at NASA. Abstract: Evaluating the advanced technology projects at NASA is difficult due to multiple and intertwined evaluation criteria and uncertainties inherent in unproven new technologies. The conventional multi-criteria decision-making models often ignore the interdependencies and uncertainties in the evaluation process. We propose a fuzzy Weighted Influence Non-linear Gauge System (WINGS) to evaluate advanced technology projects at the Kennedy Space Center (KSC). The WINGS method uses ideographic causal maps to uncover the intertwined criteria and their causal relations in complex problems. Fuzzy set theory is an effective method that uses fuzzy logic to model uncertainties in ill-defined problems. The fuzzy WINGS method proposed in this study uncovers the interdependencies among the evaluation criteria by identifying the direction of the dependencies (influences) and their intensities, along with the strengths of the evaluation criteria. Fuzzy judgments are used to cope with uncertainties in untested new technologies. The conventional WINGS method does not consider a reference point in the solution space. For this reason, we introduce the concepts of ideal and nadir solutions, which are new to WINGS, to rank the alternative solutions according to their Euclidean distances from the ideal (or nadir ) solutions. Finally, we present a case study to evaluate ten advanced technology projects based on six intertwined criteria and 38 sub-criteria at the KSC to demonstrate the applicability of the new fuzzy WINGS method proposed in this study.