Journals / Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics / 2023 / Volume: 72 Issue: 4

Renewed structure of neutrosophic soft graphs and its application in decision-making problem

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Publication Date
2023-12-29
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We also provide a comparative analysis with the existing method given in [4].

📌 3 Key Takeaways

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Objective & Hypothesis:This study is designed with the renewed concept of neutrosophic soft graph (briefly ns-graph) which is a combination of graphs and neutrosophic soft sets.
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Key Findings & Data:We re-define notions of ns-graphs and ns-subgraphs with the different perspective from the study in [4].
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Conclusion & Impact:We also provide a comparative analysis with the existing method given in [4].
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Neutrosophic soft set · graf · neutrosophic soft graph

Abstract

This study is designed with the renewed concept of neutrosophic soft graph (briefly ns-graph) which is a combination of graphs and neutrosophic soft sets. We re-define notions of ns-graphs and ns-subgraphs with the different perspective from the study in [4]. Also, we introduce some new operations on ns-graphs and detailed them with convenient examples. Moreover, we present an application of ns-graphs to determine of optimal object by using given data with the help of an algorithm. This algorithm we developed is new inventiveness domain for problems which are involving uncertainty, and effectively finds the optimal result between the states where vagueness exists. We also provide a comparative analysis with the existing method given in [4].

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Cite This Article

Çelik, Y. (2023). Renewed structure of neutrosophic soft graphs and its application in decision-making problem. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, Volume: 72 Issue: 4. https://doi.org/10.31801/cfsuasmas.1233661

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References (23)

  1. Akram, M., Dudek, W.A., Interval-valued fuzzy graphs, Computers and Mathematics with Applications, 61(2) (2011), 289–299. https://doi.org/10.1016/j.camwa.2010.11.004
  2. Akram, M., Nawaz, S., Operations on soft graphs, Fuzzy Information and Engineering, 7(4) (2015), 423–449. https://doi.org/10.1016/j.fiae.2015.11.003
  3. Akram, M., Nawaz, S., Fuzzy soft graphs with applications, Journal of Intelligent and Fuzzy Systems, 30(6) (2016), 3619–3632. https://doi.org/10.3233/IFS-162107
  4. Akram, M., Sundas, S., Neutrosophic soft graphs with application, Journal of Intelligent and Fuzzy Systems, 32(1) (2017), 841–858. https://doi.org/10.3233/JIFS-16090
  5. Atanassov, K. T., Gargov, G., Intuitionistic Fuzzy Sets: Theory and Applications, Springer Physica-Verlag, Berlin, 1999.
  6. Bhattacharya, P., Some remarks on fuzzy graphs, Pattern Recognition Letters., 6(5) (1987), 297–302. https://doi.org/10.1016/0167-8655(87)90012-2
  7. Broumi, S., Generalized neutrosophic soft set, International Journal of Computer Science, Engineering and Information Technology, 3(2) (2013), 17–30. https://doi.org/10.5121/ijcseit.2013.3202
  8. Broumi, S., Sundareswaran, R., Shanmugapriya, M., Nordo, G., Talea, M., Bakali, A., Smarandache, F., Interval-valued fermatean neutrosophic graphs, Decision Making: Applications in Management and Engineering, 5(2) (2022), 176–200. https://doi.org/10.31181/dmame0311072022b
  9. Broumi, S., Ajay, D., Chellamani, P., Malayalan, L., Talea, M., Bakali, A., Schweizer, P., Jafari, S., Interval valued pentapartitioned neutrosophic graphs with an application to MCDM, Operational Research in Engineering Sciences: Theory and Applications, 5(3) (2022) 68–91.
  10. Çelik, Y., On bipolar fuzzy soft graphs, Creative Mathematics and Informatics, 27(2) (2018), 123–132. https://doi.org/10.37193/CMI.2018.02.04
  11. Deli, I., Interval-valued neutrosophic soft sets and its decision making, International Journal of Machine Learning and Cybernetics, 8 (2015), 1–12. https://doi.org/10.1007/s13042-015-0461-3
  12. Euler, L., Solutio problematis ad geometriam situs pertinentis, Commentarii Academiae Scientiarum Imperimalis Petropolitanae, 8 (1736), 128–140.
  13. Kandasamy, W. B., Ilanthenral, K., Smarandache, F., Neutrosophic Graphs: A New Dimension to Graph Theory, EuropaNova, USA, 2015.
  14. Maji, P. K., Neutrosophic soft set, Annals of Fuzzy Mathematics and Informatics, 5(1) (2013), 157–168.
  15. Mohinta, S, Samanta, T., An introduction to fuzzy soft graphs, Mathematica Moravica, 19(2) (2015), 35–48.
  16. Mordeson J. N., Peng, C. S., Operations on fuzzy graphs, Information Sciences, 79(3-4) (1994), 159–170. https://doi.org/10.1016/0020-0255(94)90116-3
  17. Rosenfeld, A., Fuzzy graphs, Fuzzy Sets and Their Applications to Cognitive and Decision Processes, Academic Press, New York, 1975.
  18. Shah, N., Hussain, A., Neutrosophic soft graphs, Neutrosophic Sets and Systems, 11 (2016), 31–44.
  19. Smarandache, F., Neutrosophic set-a generalization of the intuitionistic fuzzy set, International Journal of Pure and Applied Mathematics, 24(3) (2005), 287–297.
  20. Thumbakara, R. K., George, B. Soft graphs, General Mathematics Notes, 21(2) (2014), 75–86.
  21. Zadeh, L. A., Fuzzy sets, Information and Control, 8(3) (1965), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
  22. Zihni, O., C¸ elik, Y., Kara, G., Interval-valued fuzzy soft graphs, Topological Algebra and its Applications, 5(1) (2017), 17–29. https://doi.org/10.1515/taa-2017-0004
  23. Broumi, S., Generalized neutrosophic soft set, International Journal of Computer Science, Engineering and Information Technology, 3(2) (2013), 17–30. https://doi.org/10.5121/ijcseit.2013.3202