A Hybrid MCDM Model for Service Composition in Cloud Manufacturing using O-TOPSIS

The purpose of this research article was to define the current or future usage of Industry 4.0 technologies (Cloud Computing, IoT, etc.) to improve industrial manufacturing. The goal of this study is to rate the options using a hybrid CRITIC - O-TOPSIS Multi Criteria Decision Making model. The CRITIC technique is used to calculate Objective Weights. Also, when comparing the findings to TOPSIS, A thorough Systematic Literature Review comes first. Secondly, a theoretical approach to recognizing the Index System of Criteria. Third, Creating a Hybrid Model of CRITIC and O-TOPSIS for Decision Making. Lastly, Comparing and Ordering Options. The proposed technique successfully addresses the ambiguity and uncertainty of heterogeneous information while maintaining assessment data accuracy. Also, because objective weights are more grounded in reality than subjective weights, the result is more precise. CRITIC approach results reveals that Ease of Opting has the most weight and Ease of Implementation has the least weight O-TOPSIS method ranks alternatives in the following order: A4>A5>A3>A1>A2. This paper ranks alternatives based on extensive 22 criteria in Service Composition in Cloud Manufacturing using the hybrid model CRITIC - O-TOPSIS

@article{Ahmed2024,
  title     = {A Hybrid MCDM Model for Service Composition in Cloud Manufacturing using O-TOPSIS},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {4},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Syed Omer Farooq Ahmed and Adapa Gopi},
  doi       = {10.14569/IJACSA.2024.0150436},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150436}
}