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Multi-criteria intuitionistic fuzzy group decision analysis with TOPSIS method for selecting appropriate cloud solution to manage big data projects

Author

Listed:
  • Nitin Sachdeva

    (University of Delhi)

  • Ompal Singh

    (University of Delhi)

  • P. K. Kapur

    (Amity University)

  • Diego Galar

    (University of Skövde)

Abstract

Today technology that learns from data to forecast future behavior of individuals, organizations, government and country as a whole, is playing a crucial role in the advancement of human race. In fact, the strategic advantage most of the companies today strive for are use of new available technologies like cloud computing and big data. However, today’s dynamic business environment poses severe challenges in front of companies as to how to make use of the power of big data with the technical flexibility that cloud computing provides? Therefore, evaluating, ranking and selecting the most appropriate cloud solution to manage big data project is a complex concern which required multi criteria decision environment. In this paper we propose a hybrid TOPSIS method combined with intuitionistic fuzzy set to select appropriate cloud solution to manage big data projects in group decision making environment. In order to collate individual opinions of decision makers for rating the importance of various criteria and alternatives, we employed intuitionistic fuzzy weighted averaging operator. Lastly sensitivity analysis is performed so as to evaluate the impact of criteria weights on final ranking of alternatives.

Suggested Citation

  • Nitin Sachdeva & Ompal Singh & P. K. Kapur & Diego Galar, 2016. "Multi-criteria intuitionistic fuzzy group decision analysis with TOPSIS method for selecting appropriate cloud solution to manage big data projects," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 7(3), pages 316-324, September.
    • Handle: RePEc:spr:ijsaem:v:7:y:2016:i:3:d:10.1007_s13198-016-0455-x
    DOI: 10.1007/s13198-016-0455-x
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    References listed on IDEAS

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