Grey relational analysis-driven optimization of neutrosophic MAGDM for cloud SaaS credibility evaluation

Abstract

In the basic cloud service delivery model, since SaaS (Software as a Service) is located at the application layer, if a relatively complete cloud service credibility comprehensive evaluation framework can be established from the perspective of SaaS cloud service consumers and combined with their trust context, it can not only effectively solve the trust problem between cloud service consumers (CSC) and cloud service provider (CSP), but also has very important practical significance for the popularization and promotion of SaaS service applications. The credibility evaluation of SaaS services in cloud computing environment is often considered as a multi-attribute group decision making (MAGDM) problem. In this paper, the grey relational analysis (GRA) method is extended to the single-valued neutrosophic sets (SVNSs) setting to deal with MAGDM with incomplete weight information. First, the SVNSs are reviewed. In addition, the single-valued neutrosophic number GRA (SVNN-GRA) is established for MAGDM with incomplete weight information, and the computational steps for all designs are listed. Finally, the credibility evaluation of SaaS services in cloud computing environment is given to demonstrate the SVNN-GRA model and some comparative analysis is done to demonstrate the SVNN-GRA.