Solving cloud vendor selection problem using intuitionistic fuzzy decision framework
| Autor: | K. Soundarapandian Ravichandran, Sanjay Kumar Tyagi, Raghunathan Krishankumar |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization VIKOR method Computer science business.industry Vendor Context (language use) Cloud computing 02 engineering and technology 020901 industrial engineering & automation Operator (computer programming) Ranking Artificial Intelligence Simple (abstract algebra) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing business Software Selection (genetic algorithm) |
| Zdroj: | Neural Computing and Applications. 32:589-602 |
| ISSN: | 1433-3058 0941-0643 |
| DOI: | 10.1007/s00521-018-3648-1 |
| Popis: | This paper presents a new decision-making framework called cloud vendor selector (CVS) for effective selection of cloud vendors by mitigating the challenge of unreasonable criteria weight assignment and improper management of uncertainty. The CVS comprises of two stages where, in the first stage, decision-makers’ intuitionistic fuzzy-valued preferences are aggregated using newly proposed extended simple Atanassov’s intuitionistic weighted geometry operator. Further, in the second stage, criteria weights are estimated by using newly proposed intuitionistic fuzzy statistical variance method and finally, ranking of cloud vendor (CV) is done using newly proposed three-way VIKOR method under intuitionistic fuzzy environment which introduces neutral category along with cost and benefit for better understanding the nature of criteria. An illustrative example of CV selection is demonstrated to show the practicality and usefulness of the proposed framework. Finally, the strength and weakness of the proposal are realized from both theoretic and numeric context by comparison with other methods. |
| Databáze: | OpenAIRE |
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