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Bipolar Interval-Valued Neutrosophic Optimization Model of Integrated Healthcare System

Sumbal Khalil1, Sajida Kousar1, Nasreen Kausar2, Muhammad Imran3, Georgia Irina Oros4,*

1 Department of Mathematics and Statistics, International Islamic University, Islamabad, Pakistan
2 Department of Mathematics, Faculty of Arts and Sciences, Yildiz Technical University, Esenler, 34210, Istanbul, Turkey
3 NUST Business School Islamabad, Pakistan
4 Department of Mathematics and Computer Science, University of Oradea, Oradea, 410087, Romania

* Corresponding Author: Georgia Irina Oros. Email:

Computers, Materials & Continua 2022, 73(3), 6207-6224.


Bipolar Interval-valued neutrosophic set is another generalization of fuzzy set, neutrosophic set, bipolar fuzzy set and bipolar neutrosophic set and thus when applied to the optimization problem handles uncertain data more efficiently and flexibly. Current work is an effort to design a flexible optimization model in the backdrop of interval-valued bipolar neutrosophic sets. Bipolar interval-valued neutrosophic membership grades are picked so that they indicate the restriction of the plausible infringement of the inequalities given in the problem. To prove the adequacy and effectiveness of the method a unified system of sustainable medical healthcare supply chain model with an uncertain figure of product complaints is used. Time, quality and cost are considered as satisfaction level to choose best supplier for medicine procurement. The proposed model ensures 99% satisfaction for cost reduction, 63% satisfaction for the quality of product and 64% satisfaction for total time taken in medicine supply chain.


Cite This Article

S. Khalil, S. Kousar, N. Kausar, M. Imran and G. I. Oros, "Bipolar interval-valued neutrosophic optimization model of integrated healthcare system," Computers, Materials & Continua, vol. 73, no.3, pp. 6207–6224, 2022.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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