期刊
NEURAL COMPUTING & APPLICATIONS
卷 32, 期 2, 页码 589-602出版社
SPRINGER LONDON LTD
DOI: 10.1007/s00521-018-3648-1
关键词
Cloud vendor; Decision making; Intuitionistic fuzzy set; Standard variance; Three-way VIKOR
资金
- University Grants Commission (UGC), India [F./2015-17/RGNF-2015-17-TAM-83]
- Department of Science and Technology (DST), India [SR/FST/ETI-349/2013]
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.
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