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Evaluation of the Performance of Search and Rescue Robots Using T-spherical Fuzzy Hamacher Aggregation Operators

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Abstract

Multi-attribute decision-making approach is a widely used algorithm that needs some aggregation tools and several such aggregation operators have been developed in past decades to serve the purpose. Hamacher aggregation operator is one such operator which is based on Hamacher t-norm and t-conorm. It is observed that the Hamacher aggregation operators of intuitionistic fuzzy set, Pythagorean fuzzy set and that of picture fuzzy set has some limitations in their applicability. To serve the purpose, in this paper, some Hamacher aggregation operators based on T-spherical fuzzy numbers are introduced. The concepts of T-spherical fuzzy Hamacher-weighted averaging and T-spherical fuzzy Hamacher-weighted geometric aggregation operators are proposed which described four aspects of human opinion including yes, no, abstinence and refusal with no limitations. Such type of aggregation operators efficiently describes the cases that left unsolved by the existing aggregation operators. The validity of the proposed aggregation operators is examined, and some basic properties are discussed. The proposed new Hamacher aggregation operators are used to analyze the performance of search and rescue robots using a multi-attribute decision-making approach as their performance in an emergency is eminent. The proposed Hamacher aggregation operators have two variable parameters, namely q and \(\gamma \) which affects the decision-making process and their sensitivity towards decision-making results is analyzed. A comparative analysis of the results obtained using proposed Hamacher aggregation operators in view of the variable parameters q and \(\gamma \) is established to discuss any advantages or disadvantages.

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References

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  3. Yager, R.R.: Pythagorean fuzzy subsets. In: IFSA world congress and NAFIPS annual meeting (IFSA/NAFIPS), 2013 Joint. IEEE. (2013) https://doi.org/10.1109/IFSA-NAFIPS.2013.6608375

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

    Article  Google Scholar 

  5. Cường, B.C.: Picture fuzzy sets. J. Comput. Sci. Cybern. 30(4), 409–420 (2014)

    Google Scholar 

  6. Mahmood, T., Ullah, K., Khan, Q., Jan, N.: An approach towards decision making and medical diagnosis problems using the concept of spherical fuzzy sets. Neural Comput. Appl. 31, 7041–7053 (2019)

    Article  Google Scholar 

  7. Xu, Z.: Intuitionistic fuzzy aggregation operators. IEEE Trans. Fuzzy Syst. 15(6), 1179–1187 (2007)

    Article  Google Scholar 

  8. Xu, Z., Yager, R.R.: Some geometric aggregation operators based on intuitionistic fuzzy sets. Int. J. Gen. Syst. 35(4), 417–433 (2006)

    Article  MathSciNet  Google Scholar 

  9. Garg, H.: Novel intuitionistic fuzzy decision making method based on an improved operation laws and its application. Eng. Appl. Artif. Intell. 60, 164–174 (2017)

    Article  Google Scholar 

  10. Peng, X., Yang, Y.: Some results for Pythagorean fuzzy sets. Int. J. Intell. Syst. 30(5), 1133–1160 (2015)

    Article  Google Scholar 

  11. 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 

  12. Garg, H.: Some picture fuzzy aggregation operators and their applications to multicriteria decision-making. Arab. J. Sci. Eng. 42(12), 5275–5290 (2017)

    Article  MathSciNet  Google Scholar 

  13. Wang, C., Zhou, X., Tu, H., Tao, S.: Some geometric aggregation operators based on picture fuzzy sets and their application in multiple attribute decision making. Italian J. Pure Appl. Math. 37, 477–492 (2017)

    MathSciNet  MATH  Google Scholar 

  14. Wang, W., Liu, X.: Intuitionistic fuzzy geometric aggregation operators based on Einstein operations. Int. J. Intell. Syst. 26(5), 1049–1075 (2011)

    Article  Google Scholar 

  15. Zhao, X., Wei, G.: Some intuitionistic fuzzy Einstein hybrid aggregation operators and their application to multiple attribute decision making. Knowl. Based Syst. 37, 472–479 (2013)

    Article  Google Scholar 

  16. Garg, H.: Generalized Pythagorean fuzzy geometric aggregation operators using Einstein t-norm and t-conorm for multicriteria decision-making process. Int. J. Intell. Syst. 32(6), 597–630 (2017)

    Article  Google Scholar 

  17. Garg, H.: A new generalized Pythagorean fuzzy information aggregation using Einstein operations and its application to decision making. Int. J. Intell. Syst. 31(4), 886–920 (2016)

    Article  Google Scholar 

  18. Kaur, G., Garg, H.: Generalized cubic intuitionistic fuzzy aggregation operators using t-norm operations and their applications to group decision-making process. Arab. J. Sci. Eng. 44(3), 2775–2794 (2019)

    Article  Google Scholar 

  19. Liu, P., Khan, Q., Mahmood, T., Hassan, N.: T-spherical fuzzy power Muirhead mean operator based on novel operational laws and their application in multi-attribute group decision making. IEEE Access 7, 22613–22632 (2019)

    Article  Google Scholar 

  20. Garg, H., Munir, M., Ullah, K., Mahmood, T., Jan, N.: Algorithm for T-spherical fuzzy multi-attribute decision making based on improved interactive aggregation operators. Symmetry 10(12), 670 (2018). https://doi.org/10.3390/sym10120670

    Article  Google Scholar 

  21. Ullah, K., Mahmood, T., Jan, N.: Similarity measures for T-spherical fuzzy sets with applications in pattern recognition. Symmetry 10(6), 193 (2018). https://doi.org/10.3390/sym10060193

    Article  MATH  Google Scholar 

  22. Quek, S.G., Selvachandran, G., Munir, M., Mahmood, T., Ullah, K., Son, L.H., Thong, P.H., Kumar, R., Priyadarshini, I.: Multi-attribute multi-perception decision-making based on generalized T-spherical fuzzy weighted aggregation operators on neutrosophic sets. Mathematics 7(4), 780 (2019). https://doi.org/10.3390/math7090780

    Article  Google Scholar 

  23. Ullah, K., Garg, H., Mahmood, T., Jan, N., Ali, Z.: Correlation coefficients for T-spherical fuzzy sets and their applications in clustering and multi-attribute decision making. Soft Comput 24(3), 1647–1659 (2020). https://doi.org/10.1007/s00500-019-03993-6

    Article  MATH  Google Scholar 

  24. Oussalah, M.: On the use of Hamacher’s t-norms family for information aggregation. Inf. Sci. 153, 107–154 (2003)

    Article  MathSciNet  Google Scholar 

  25. Huang, J.Y.: Intuitionistic fuzzy Hamacher aggregation operators and their application to multiple attribute decision making. J. Intell. Fuzzy Syst. 27(1), 505–513 (2014)

    Article  MathSciNet  Google Scholar 

  26. Liu, P.: Some Hamacher aggregation operators based on the interval-valued intuitionistic fuzzy numbers and their application to group decision making. IEEE Trans. Fuzzy Syst. 22(1), 83–97 (2013)

    Article  Google Scholar 

  27. Garg, H.: Intuitionistic fuzzy hamacher aggregation operators with entropy weight and their applications to multi-criteria decision-making problems. Iran. J. Sci. Technol. Trans. Electr. Eng. 43(3), 597–613 (2019)

    Article  Google Scholar 

  28. Wu, S.J., Wei, G.W.: Pythagorean fuzzy Hamacher aggregation operators and their application to multiple attribute decision making. Int. J. Knowl. Based Intell. Eng. Syst. 21(3), 189–201 (2017)

    Google Scholar 

  29. Gao, H.: Pythagorean fuzzy hamacher prioritized aggregation operators in multiple attribute decision making. J. Intell. Fuzzy Syst. 35(2), 2229–2245 (2018)

    Article  Google Scholar 

  30. Wei, G.W.: Pythagorean fuzzy Hamacher power aggregation operators in multiple attribute decision making. Fundam. Inf. 166(1), 57–85 (2019)

    Article  MathSciNet  Google Scholar 

  31. Darko, A.P., Liang, D.: Some q-rung orthopair fuzzy Hamacher aggregation operators and their application to multiple attribute group decision making with modified EDAS method. Eng. Appl. Artif. Intell. 87, 103259 (2020)

    Article  Google Scholar 

  32. Wei, G.: Picture fuzzy Hamacher aggregation operators and their application to multiple attribute decision making. Fundam. Inf. 157(3), 271–320 (2018)

    Article  MathSciNet  Google Scholar 

  33. Jana, C., Pal, M.: Assessment of enterprise performance based on picture fuzzy hamacher aggregation operators. Symmetry 11(1), 75 (2019)

    Article  Google Scholar 

  34. Murphy, R.R., Tadokoro, S., Nardi, D., Jacoff, A., Fiorini, P., Choset, H., Erkmen, A.M.: Search and rescue robotics. Springer handbook of Robotics pp. 1151–1173 (2008). https://doi.org/10.1007/978-3-540-30301-5_51

  35. Zhou, J., Baležentis, T., Streimikiene, D.: Normalized weighted Bonferroni Harmonic mean-based intuitionistic fuzzy operators and their application to the sustainable selection of search and rescue robots. Symmetry 11(2), 218 (2019). https://doi.org/10.3390/sym11020218

    Article  MATH  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. Garg, H., Kumar, K.: A novel possibility measure to interval-valued intuitionistic fuzzy set using connection number of set pair analysis and their applications. Neural Comput. Appl. (2019). https://doi.org/10.1007/s00521-019-04291-w

    Article  Google Scholar 

  38. Wang, L., Garg, H., Li, N.: Interval-valued q-rung orthopair 2-tuple linguistic aggregation operators and their applications to decision making process. IEEE Access 7(1), 131962–131977 (2019)

    Article  Google Scholar 

  39. Garg, H.: Nancy, linguistic single-valued neutrosophic power aggregation operators and their applications to group decision-making problems. IEEE CAA J. Autom. Sin. (2019). https://doi.org/10.1109/JAS.2019.1911522

    Article  Google Scholar 

  40. Garg, H., Kaur, G.: Quantifying gesture information in brain hemorrhage patients using probabilistic dual hesitant fuzzy sets with unknown probability information. Comput. Ind. Eng. 140, 106211 (2020). https://doi.org/10.1016/j.cie.2019.106211

    Article  Google Scholar 

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Correspondence to Harish Garg.

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Ullah, K., Mahmood, T. & Garg, H. Evaluation of the Performance of Search and Rescue Robots Using T-spherical Fuzzy Hamacher Aggregation Operators. Int. J. Fuzzy Syst. 22, 570–582 (2020). https://doi.org/10.1007/s40815-020-00803-2

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  • DOI: https://doi.org/10.1007/s40815-020-00803-2

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