A hybrid MCDM model for service composition in cloud manufacturing using BWM-Critic-TOPSIS-TODIM

Cloud services reflect an information revolution that is transforming enterprise computer utilisation capabilities. Then, the reasons why organisations plan to employ a cloud service(s) must be discovered and studied to lead providers in improving new and creative activities. Communication between providers and customers becomes more convenient in the Cloud Manufacturing environment. This article ranks alternatives, criteria, and sub-criteria using multi-criteria decision-making algorithms. Then weights for criteria were calculated using Best Worst Method and Criteria Importance. Inter-criteria Correlation (CRITIC). These weights are used in the model to account for human judgment and the value of raw data. The Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) is used to rate the available options. The TODIM approach is used to process and rank heterogeneous assessment data. The rankings from TOPSIS and TODIM are compared. We can conclude that the proposed hybrid model for alternative ranking is effective and reliable too, based on comparative analysis and sensitive analysis.