A hybrid MCDM model for service composition in cloud manufacturing using BWM-critic-topsis-todim | [ARPN Journal of Engineering and Applied Sciences • 2024]

Author(s):

1. Syed Omer Farooq Ahmed: Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation,Guntur,India

2. Adapa Gopi: Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation,Guntur,India

Abstract:

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 decisionmaking algorithms. Then weights for criteria were calculated using Best Worst Method and Criteria Importance. Intercriteria 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.

Page(s): 707-721

DOI: DOI not available

Published: Journal: ARPN Journal of Engineering and Applied Sciences, Volume: 19, Issue: 11, Year: 2024

Keywords:

Sensitivity Analysis , TODIM method , BWM , CRITIC method , cloud manufacturing CMFg , service composition , TOPSIS method

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