Ranking of Cloud Services by applying BWM-TOPSIS, BWM-ARAS, and BWM-COPRAS Hybrid MCDM Methods

Abstract

Abstract The cloud computing business is a global industry with a multitude of cloud service providers. Customers may utilize the MCDM approach to appraise and analyze cloud service providers (CSPs) according to their requirements. This study presents a proposal for utilizing hybrid Multiple Criteria Decision Making (MCDM) methodologies. A hybrid Multiple Criteria Decision Making (MCDM) technique has been created to evaluate and rank cloud service providers using use-case scenarios. The hybrid approach has two components. Initially, we employ the Best Worst Method (BWM) weighting estimate technique to compute the criterion weights and relative scores of CSPs. Next, we utilize the TOPSIS, ARAS, and COPRAS techniques to evaluate and rank the cloud service provider. We illustrate the effectiveness and capabilities of hybrid approaches for evaluating cloud service providers through a use-case scenario. The proposed methods are compared, and it is found that outcomes are more or less the same, and ranking results of CSPs are almost identical using the different quantity of criteria and CSPs. We compared the recommended methods to commonly used AHP, and results indicate that suggested approach is more efficient than AHP. The suggested method requires fewer pairwise comparisons compared to AHP, which uses a different set of criteria.