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<p>The cloud computing business is a global industry with many cloud service providers. Customers may utilize the MCDM approach to appraise and analyze cloud service providers (CSPs) according to their requirements. This study proposes 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 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 the ranking results of CSPs are almost identical to ARAS and COPRAS. Still, there is a slight change in the ranking of TOPSIS using the different quantity of criteria and CSPs. We compared the recommended methods to commonly used AHP, and the results indicate that the suggested approach is more efficient than AHP. The suggested method requires fewer pairwise comparisons compared to AHP, which uses a different set of criteria.</p>

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Ranking of cloud services by applying BWM-TOPSIS, BWM-ARAS, and BWM-COPRAS hybrid MCDM methods

  • 期刊论文

  • 发表日期：

    2025年4月10日

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  • Anupama Mishra,
  • Rakesh Kumar

摘要

The cloud computing business is a global industry with many cloud service providers. Customers may utilize the MCDM approach to appraise and analyze cloud service providers (CSPs) according to their requirements. This study proposes 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 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 the ranking results of CSPs are almost identical to ARAS and COPRAS. Still, there is a slight change in the ranking of TOPSIS using the different quantity of criteria and CSPs. We compared the recommended methods to commonly used AHP, and the results indicate that the suggested approach is more efficient than AHP. The suggested method requires fewer pairwise comparisons compared to AHP, which uses a different set of criteria.