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Analysis of Social Networks, Communication Networks and Shortest Path Problems in the Environment of Interval-Valued q-Rung Ortho Pair Fuzzy Graphs

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Abstract

The ideas of q-rung ortho pair fuzzy set (q-ROPFS) and interval-valued q-rung ortho pair fuzzy set (IVq-ROPFS) are two major recent developments in the field of fuzzy set theory. A q-ROPFS and IVq-ROPFS improved the limited structures of Pythagorean fuzzy set, intuitionistic fuzzy set as well as fuzzy set by improving the conditions that makes these concepts restricted. The goal of this research is to introduce a new notion of interval-valued q-rung ortho pair fuzzy graph (IVQ-ROPFG) and to study the related graphical terms such as subgraph, complement, degree of vertices and path etc. Each of the graphical concept is demonstrated with an example. Another valuable contribution of this manuscript is the modeling of some traffic networks, telephone networks and social networks using the concepts of IVQ-ROPFGs. First, the famous problem of finding a shortest path in a traffic network is studied using two different approaches. A study of social network describing the strength of co-authorship between different researchers from several countries is also established using the concept of IVq-ROPFGs. Finally, a telephone networking problem is demonstrated showing the calling ratios of incoming and outgoing calls among a group of people. Two engineering decision-making problems are also studied using some aggregation operators and the concepts of IVq-ROPFGs. Through comparative study, the advantages of working in the environment of IVq-ROPFG are specified.

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References

  1. Akram, M., Dudek, W.A.: Intuitionistic fuzzy hypergraphs with applications. Inf. Sci. 218, 182–193 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  2. Akram, M., Luqman, A.: Certain networks models using single-valued neutrosophic directed hypergraphs. J. Intell. Fuzzy Syst. 33(1), 575–588 (2017)

    Article  MATH  Google Scholar 

  3. Akram, M., Adeel, A.: m-polar fuzzy graphs and m-polar fuzzy line graphs. J. Discrete Math. Sci. Cryptogr. 20(8), 1597–1617 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  4. Akram, M., Dudek, W.A.: Interval-valued fuzzy graphs. Comput. Math. Appl. 61(2), 289–299 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  5. Atanassov, K.T.: Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20(1), 87–96 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  6. Atanassov, K., Gargov, G.: Interval valued intuitionistic fuzzy sets. Fuzzy Sets Syst. 31(3), 343–349 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  7. Bisen, D., Sharma, S.: An energy-efficient routing approach for performance enhancement of MANET through adaptive neuro-fuzzy inference system. Int. J. Fuzzy Syst. 20(8), 2693–2708 (2018)

    Article  Google Scholar 

  8. Bharati, S.K., Singh, S.R.: Transportation problem under interval-valued intuitionistic fuzzy environment. Int. J. Fuzzy Syst. 20(5), 1511–1522 (2018)

    Article  Google Scholar 

  9. Broumi, S., Bakali, A., Talea, M., Smarandache, F., Vladareanu, L. (eds.): Computation of shortest path problem in a network with SV-trapezoidal neutrosophic numbers. In: 2016 International Conference on Advanced Mechatronic Systems (ICAMechS). IEEE (2016)

  10. Broumi, S., Bakal, A., Talea, M., Smarandache, F., Vladareanu, L. (eds.): Applying Dijkstra algorithm for solving neutrosophic shortest path problem. In: 2016 International Conference on Advanced Mechatronic Systems (ICAMechS). IEEE (2016)

  11. Broumi, S., Ullah, K., Bakali, A., Talea, M., Singh, P.K., Mahmood, T., et al.: Novel system and method for telephone network planing based on neutrosophic graph. Glob. J. Comput. Sci. Technol. 18(2), 1–10 (2018)

    Google Scholar 

  12. Chen, W.J., Jhong, B.G., Chen, M.Y.: Design of path planning and obstacle avoidance for a wheeled mobile robot. Int. J. Fuzzy Syst. 18(6), 1080–1091 (2016)

    Article  MathSciNet  Google Scholar 

  13. Davvaz, B., Jan, N., Mahmood, T., Ullah, K.: Intuitionistic fuzzy graphs of nth type with applications. J. Intell. Fuzzy Syst. (2018). https://doi.org/10.3233/jifs-181123.accepted

    Article  Google Scholar 

  14. Deng, Y., Chen, Y., Zhang, Y., Mahadevan, S.: Fuzzy Dijkstra algorithm for shortest path problem under uncertain environment. Appl. Soft Comput. 12(3), 1231–1237 (2012)

    Article  Google Scholar 

  15. Dou, Y., Zhu, L., Wang, H.S.: Solving the fuzzy shortest path problem using multi-criteria decision method based on vague similarity measure. Appl. Soft Comput. 12(6), 1621–1631 (2012)

    Article  Google Scholar 

  16. Gorzałczany, M.B.: A method of inference in approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets Syst. 21(1), 1–17 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  17. Jan, N., Zedam, L., Mahmood, T., Ullah, K., Davvaz, B., Ali, Z.: An improved clustering algorithm for picture fuzzy graphs and its applications in human decision making. Int. J. Fuzzy Syst. (2018). https://doi.org/10.1007/s40815-019-00634-w

    Article  Google Scholar 

  18. Joshi, B.P., Singh, A., Bhatt, P.K., Vaisla, K.S.: Interval valued q-rung orthopair fuzzy sets and their properties. J. Intell. Fuzzy Syst. 1–6 (2018) (Pre-press)

  19. Kaufmann, A.: Introduction à la théorie des sous-ensembles flous à l’usage des ingénieurs: Éléments théoriques de base: Masson (1973)

  20. Khorsandi, A., Liu, X.-C., Cao, B.-Y.: A new algorithm to shortest path problem with fuzzy arc lengths. In: International Workshop on Mathematics and Decision Science. Springer (2016)

  21. Liu, P., Wang, P.: Some q-rung orthopair fuzzy aggregation operators and their applications to multiple-attribute decision making. Int. J. Intell. Syst. 33(2), 259–280 (2018)

    Article  Google Scholar 

  22. Liu, P., Liu, W.: Scaled prioritized operators based on the linguistic intuitionistic fuzzy numbers and their applications to multi-attribute decision making. Int. J. Fuzzy Syst. 20(5), 1539–1550 (2018)

    Article  MathSciNet  Google Scholar 

  23. Liu, P., Mahmood, T., Khan, Q.: Group decision making based on power Heronian aggregation operators under linguistic neutrosophic environment. Int. J. Fuzzy Syst. 20(3), 970–985 (2018)

    Article  MathSciNet  Google Scholar 

  24. Liu, P., Zhang, X.: Some Maclaurin symmetric mean operators for single-valued trapezoidal neutrosophic numbers and their applications to group decision making. Int. J. Fuzzy Syst. 20(1), 45–61 (2018)

    Article  MathSciNet  Google Scholar 

  25. Liu, P., Liu, X.: Multi-attribute group decision-making method based on cloud distance operators with linguistic information. Int. J. Fuzzy Syst. 19(4), 1011–1024 (2017)

    Article  MathSciNet  Google Scholar 

  26. Mougouei, D., Powers, D.M.: Modeling and selection of interdependent software requirements using fuzzy graphs. Int. J. Fuzzy Syst. 19(6), 1812–1828 (2017)

    Article  MathSciNet  Google Scholar 

  27. Mishra, S., Pal, A.: Product of interval valued intuitionistic fuzzy graph. Ann. Pure Appl. Math. 5(1), 37–46 (2013)

    Google Scholar 

  28. Mordeson, J.N., Mathew, S.: t-norm fuzzy graphs. New Math. Nat. Comput. 14(01), 129–143 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  29. Naz, S., Rashmanlou, H., Malik, M.A.: Operations on single valued neutrosophic graphs with application. J. Intell. Fuzzy Syst. 32(3), 2137–2151 (2017)

    Article  MATH  Google Scholar 

  30. Narayanamoorthy, S., Karthick, P.: The intuitionistic fuzzy set approach for gray level image thresholding using normalized graph cuts. Int. J. Pure Appl. Math. 113(8), 104–112 (2017)

    Google Scholar 

  31. Naz, S., Ashraf, S., Akram, M.: A novel approach to decision-making with Pythagorean fuzzy information. Mathematics 6(6), 95 (2018)

    Article  MATH  Google Scholar 

  32. Parvathi, R., Karunambigai, M.: Intuitionistic fuzzy graphs. In: Reusch B (ed.) Computational Intelligence, Theory and Applications. Springer, pp. 139–150 (2006)

  33. Peng, X., Yang, Y.: Fundamental properties of interval-valued Pythagorean fuzzy aggregation operators. Int. J. Intell. Syst. 31(5), 444–487 (2016)

    Article  Google Scholar 

  34. Sabri, M.F.M., Danapalasingam, K.A., Rahmat, M.F.A.: Improved fuel economy of through-the-road hybrid electric vehicle with fuzzy logic-based energy management strategy. Int. J. Fuzzy Syst. 20(8), 2677–2692 (2018)

    Article  Google Scholar 

  35. Selvachandran, G., Garg, H., Alaroud, M.H., Salleh, A.R.: Similarity measure of complex vague soft sets and its application to pattern recognition. Int. J. Fuzzy Syst. 20(6), 1901–1914 (2018)

    Article  MathSciNet  Google Scholar 

  36. Ullah, K., Hassan, N., Mahmood, T., Jan, N., Hassan, M.: Evaluation of investment policy based on multi-attribute decision-making using interval valued t-spherical fuzzy aggregation operators. Symmetry 11(3), 357 (2019). https://doi.org/10.3390/sym11030357

    Article  Google Scholar 

  37. Wang, N., Sun, Z., Su, S.F., Wang, Y.: Fuzzy uncertainty observer-based path-following control of underactuated marine vehicles with unmodeled dynamics and disturbances. Int. J. Fuzzy Syst. 20(8), 2593–2604 (2018)

    Article  MathSciNet  Google Scholar 

  38. Yager, R.R.: Pythagorean fuzzy subsets. In: 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS). IEEE (2013)

  39. Yager, R.R.: Generalized orthopair fuzzy sets. IEEE Trans. Fuzzy Syst. 25(5), 1222–1230 (2017)

    Article  Google Scholar 

  40. Ye, J.: Single-valued neutrosophic minimum spanning tree and its clustering method. J. Intell. Syst. 23(3), 311–324 (2014)

    Google Scholar 

  41. Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)

    Article  MATH  Google Scholar 

Download references

Acknowledgements

This work is partially supported by Higher Education Commission (HEC) of Pakistan, under National Research Program for Universities (NRPU), Grant. No: 5833/Federal/NRPU/R&D/HEC/2016.

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Correspondence to Naeem Jan.

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Jan, N., Mahmood, T., Zedam, L. et al. Analysis of Social Networks, Communication Networks and Shortest Path Problems in the Environment of Interval-Valued q-Rung Ortho Pair Fuzzy Graphs. Int. J. Fuzzy Syst. 21, 1687–1708 (2019). https://doi.org/10.1007/s40815-019-00643-9

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  • DOI: https://doi.org/10.1007/s40815-019-00643-9

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