Journal of Medical Systems

, 43:38 | Cite as

A Group Decision Making Framework Based on Neutrosophic TOPSIS Approach for Smart Medical Device Selection

  • Mohamed Abdel-BassetEmail author
  • Gunasekaran Manogaran
  • Abduallah Gamal
  • Florentin Smarandache
Systems-Level Quality Improvement
Part of the following topical collections:
  1. Wearable Computing Techniques for Smart Health


Advances in the medical industry has become a major trend because of the new developments in information technologies. This research offers a novel approach for estimating the smart medical devices (SMDs) selection process in a group decision making (GDM) in a vague decision environment. The complexity of the selected decision criteria for the smart medical devices is a significant feature of this analysis. To simulate these processes, a methodology that combines neutrosophics using bipolar numbers with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) under GDM is suggested. Neutrosophics with TOPSIS approach is applied in the decision making process to deal with the vagueness, incomplete data and the uncertainty, considering the decisions criteria in the data collected by the decision makers (DMs). In this research, the stress is placed upon the choosing of sugar analyzing smart medical devices for diabetics’ patients. The main objective is to present the complications of the problem, raising interest among specialists in the healthcare industry and assessing smart medical devices under different evaluation criteria. The problem is formulated as a multi criteria decision type with seven alternatives and seven criteria, and then edited as a multi criteria decision model with seven alternatives and seven criteria. The results of the neutrosophics with TOPSIS model are analyzed, showing that the competence of the acquired results and the rankings are sufficiently stable. The results of the suggested method are also compared with the neutrosophic extensions AHP and MOORA models in order to validate and prove the acquired results. In addition, we used the SPSS program to check the stability of the variations in the rankings by the Spearman coefficient of correlation. The selection methodology is applied on a numerical case, to prove the validity of the suggested approach.


Bipolar neutrosophic numbers Smart medical devices Group decision making TOPSIS method Multi criteria decision making 


Compliance with Ethical Standards

Conflict of Interest

The authors declared that we do not have any conflict of interest for this research work. This article does not contain any studies with human participants or animals performed by any of the authors.


  1. 1.
    Ho, W., Xu, X., and Dey, P. K., Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research 202(1):16–24, 2010. Scholar
  2. 2.
    Joshi, D., and Kumar, S., Interval-valued intuitionistic hesitant fuzzy Choquet integral based TOPSIS method for multi-criteria group decision making. European Journal of Operational Research 248(1):183–191, 2016. Scholar
  3. 3.
    Kharal, A., A Neutrosophic multi-criteria decision making method. New Mathematics and Natural Computation 10(02):143–162, 2014. Scholar
  4. 4.
    Liang, R., Wang, J., and Zhang, H., A multi-criteria decision-making method based on single-valued trapezoidal neutrosophic preference relations with complete weight information. Neural Computing and Applications., 2017.
  5. 5.
    Smarandache, F., Neutrosophic set - a generalization of the intuitionistic fuzzy set. 2006 IEEE International Conference on Granular Computing, n.d.
  6. 6.
    Abdel-Basset, M., Zhou, Y., Mohamed, M., and Chang, V., A group decision making framework based on neutrosophic VIKOR approach for e-government website evaluation. Journal of Intelligent & Fuzzy Systems 34(6):4213–4224, 2018. Scholar
  7. 7.
    Abdel-Basset, M., Manogaran, G., Mohamed, M., and Chilamkurti, N., Three-way decisions based on neutrosophic sets and AHP-QFD framework for supplier selection problem. Future Generation Computer Systems 89:19–30, 2018. Scholar
  8. 8.
    Abdel-Basset, M., Manogaran, G., Gamal, A., and Smarandache, F., A hybrid approach of neutrosophic sets and DEMATEL method for developing supplier selection criteria. Design Automation for Embedded Systems., 2018.
  9. 9.
    Abdel-Basset, M., Mohamed, M., Hussien, A.-N., and Sangaiah, A. K., A novel group decision-making model based on triangular neutrosophic numbers. Soft Computing., 2017.
  10. 10.
    Shih, H.-S., Shyur, H.-J., and Lee, E. S., An extension of TOPSIS for group decision making. Mathematical and Computer Modelling 45(7–8):801–813, 2007. Scholar
  11. 11.
    Hwang, C. L., and Yoon, K., Multiple attribute decision making-methods and application. New York: Springer, 1981.CrossRefGoogle Scholar
  12. 12.
    Saaty, T. L., Decision making with the analytic hierarchy process. International Journal of Services Sciences 1(1):83, 2008. Scholar
  13. 13.
    Brauers, W. K. M., and Zavadskas, E. K., Project management by multimoora as an instrument for transition economies. Technological and Economic Development of Economy 16(1):5–24, 2010. Scholar
  14. 14.
    Brauers, W. K. et al., The MOORA method and its application to privatization in a transition economy. Control Cybern. 2006(35):445–469, 2006.Google Scholar
  15. 15.
    Zadeh, L. A., Fuzzy sets. Inf Control 8:338–353, 1965.CrossRefGoogle Scholar
  16. 16.
    Atanassov, K., Intuitionistic fuzzy sets. Fuzzy Sets Syst 20:87–96, 1986.CrossRefGoogle Scholar
  17. 17.
    F. Smarandache, A Unifying Field in Logics: Neutrosophic Logic. Neutrosophy, Neutrosophic Set, Neutrosophic Probability: Neutrosophic Logic. Neutrosophy, Neutrosophic Set, Neutrosophic Probability: Infinite Study, 2005.Google Scholar
  18. 18.
    Abdel-Basset, M., Mohamed, M., and Chang, V., NMCDA: A framework for evaluating cloud computing services. Future Generation Computer Systems 86:12–29, 2018. Scholar
  19. 19.
    Abdel-Basset, M., Mohamed, M., and Smarandache, F., A hybrid Neutrosophic group ANP-TOPSIS framework for supplier selection problems. Symmetry 10(6):226, 2018. Scholar
  20. 20.
    Abdel-Basset, M. G., Mohamed, M., and Smarandache, F., A novel method for solving the fully neutrosophic linear programming problems. Neural Computing and Applications:1–11.Google Scholar
  21. 21.
    Abdel-Basset, M., Gunasekaran, M., Mohamed, M., and Chilamkurti, N., A framework for risk assessment, management and evaluation: Economic tool for quantifying risks in supply chain. Future Generation Computer Systems 90:489–502, 2019.CrossRefGoogle Scholar
  22. 22.
    Abdel-Basset, M., Mohamed, M., and Sangaiah, A. K., Neutrosophic AHP-Delphi group decision making model based on trapezoidal neutrosophic numbers. Journal of Ambient Intelligence and Humanized Computing:1–17, 2017.
  23. 23.
    Basset, M. A., Mohamed, M., Sangaiah, A. K., and Jain, V., An integrated neutrosophic AHP and SWOT method for strategic planning methodology selection. Benchmarking: An International Journal 25(7):2546–2564, 2018.CrossRefGoogle Scholar
  24. 24.
    Abdel-Basset, M., and Mohamed, M., The role of single valued neutrosophic sets and rough sets in smart city: Imperfect and incomplete information systems. Measurement 124:47–55, 2018.CrossRefGoogle Scholar
  25. 25.
    Abdel-Basset, M., Mohamed, M., and Smarandache, F., An extension of Neutrosophic AHP–SWOT analysis for strategic planning and decision-making. Symmetry 10(4):116, 2018.CrossRefGoogle Scholar
  26. 26.
    Abdel-Basset, M., Mohamed, M., Smarandache, F., and Chang, V., Neutrosophic association rule mining algorithm for big data analysis. Symmetry 10(4):106, 2018.CrossRefGoogle Scholar
  27. 27.
    Chang, V., Abdel-Basset, M., and Ramachandran, M., Towards a reuse strategic decision pattern framework–from theories to practices. Information Systems Frontiers:1–18, 2018.Google Scholar
  28. 28.
    Gallego Lupiáñez, F., Interval neutrosophic sets and topology. Kybernetes 38(3/4):621–624, 2009. Scholar
  29. 29.
    Metwalli, M. A. B., Atef, A., and Smarandache, F., A hybrid Neutrosophic multiple criteria group decision making approach for project selection. Cognitive Systems Research., 2018.
  30. 30.
    Wang, H., Smarandache, F., Zhang, Y. Q., and Sunderraman, R., Single valued neutrosophic sets. Multispace and Multistructure 4:10–413, 2010.Google Scholar
  31. 31.
    Peng, J., Wang, J., Wang, J., Zhang, H., and Chen, X., Simplified neutrosophic sets and their applications in multi-criteria group decision-making problems. International Journal of Systems Science 47(10):2342–2358, 2015. Scholar
  32. 32.
    Manemaran, S. and B. J. I. J. o. C. A. Chellappa (2010). Structures on bipolar fuzzy groups and bipolar fuzzy D-ideals under (T, S) norms. International Journal of Computer Applications, 9(12): 7–10.Google Scholar
  33. 33.
    Adalı, E. A., and Işık, A. T., The multi-objective decision making methods based on MULTIMOORA and MOOSRA for the laptop selection problem. Journal of Industrial Engineering International 13:229–237, 2017.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Mohamed Abdel-Basset
    • 1
    Email author
  • Gunasekaran Manogaran
    • 2
  • Abduallah Gamal
    • 1
  • Florentin Smarandache
    • 3
  1. 1.Department of Operations Research, Faculty of Computers and InformaticsZagazig UniversitySharqiyahEgypt
  2. 2.University of CaliforniaDavisUSA
  3. 3.Math & Science DepartmentUniversity of New MexicoGallupUSA

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