Skip to main content
Log in

An advanced similarity measure for Pythagorean fuzzy sets and its applications in transportation problem

  • Published:
Artificial Intelligence Review Aims and scope Submit manuscript

Abstract

Uncertainty is excessively a common, inevitable, and conspicuopus aspect of any decision-making process, including transportation problems. Since its inception, a plethora of uncertainty representation methods has been put forward to deal with uncertainty by various researchers. Among those, fuzzy set and Intuitionistic fuzzy set is remarkably effective representation methods of uncertainty modeling. However, the existing uncertainty modeling methods have some severe limitations. Consequently, here we adopt the concept of the Pythagorean fuzzy set, an extension of the intuitionistic fuzzy set for its extensive flexibility characteristic and advantages. On the other hand, the similarity measure plays a crucial role in transportation problems under uncertainty. Therefore, we strive to introduce an advanced similarity measure of Pythagorean fuzzy sets. The proposed similarity measure is constructed based on the distances of the degree of membership, non-membership, and hesitancy of Pythagorean fuzzy sets. The present similarity measure also holds the general axioms of the similarity measure. Furthermore, we adopt some numerical examples to showcase the superiority of the proposed similarity measure and apply it to solve transportation problems. The core motive for transportation problems is minimizing transportation costs, and hence, we modified Monalisa’s method of Pythagorean fuzzy sets with the help of the proposed similarity measure. The proposed method has been demonstrated with an example and compared its output with the other pre-existing methods available in the literature. At length, statistical tests and result analysis are drawn to judge the significance of the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

Data availability

Not applicable.

References

  • Agheli B, Firozja MA, Garg H (2022) Similarity measure for Pythagorean fuzzy sets and application on multiple criteria decision making. J Stat Manag Syst 25(4):749–769. https://doi.org/10.1080/09720510.2021.1891699

    Article  Google Scholar 

  • Alves IC, Yamakami A, Gomide F (1995). An approach for fuzzy linear multicommodity transportation problems and its application. In: Proceedings of 1995 IEEE international conference on fuzzy systems, vol 2, pp 773–780. IEEE

  • Arsham H, Kahn AB (1989) A simplex-type algorithm for generaltransportation problems: an alternative to stepping-stone. J Oper Res Soc 40(6):581–590

    Article  MATH  Google Scholar 

  • Atanassov KT (1999) Intuitionistic fuzzy sets. In: Intuitionistic fuzzy sets Physica, Heidelberg, pp 1–137

  • Bharathi SD, Kanmani G (2022) Solving Pythagorean transportation problem using ArithmeticC Mean and Harmoni mean. Int J Mech Eng 7

  • Bharati SK (2021) Transportation problem with interval-valued intuitionistic fuzzy sets: impact of a new ranking. Progr Artif Intell 10(2):129–145

    Article  MathSciNet  Google Scholar 

  • Boora R, Tomar VP (2022) Two trigonometric intuitionistic fuzzy similarity measures. Int J Decis Support Syst Technol (IJDSST) 14(1):1–23

    Article  Google Scholar 

  • Boran FE, Akay D (2014) A biparametric similarity measure on intuitionistic fuzzy sets with applications to pattern recognition. Inf Sci 255:45–57

    Article  MathSciNet  MATH  Google Scholar 

  • Chen SM, Chang CH (2015) A novel similarity measure between Atanssov’s intuitionistic fuzzy sets based on transformation techniques with applications to pattern recognition. Inf Sci 291:96–114

    Article  Google Scholar 

  • Chen SM (1997) Similarity measures between vague sets and between elements. IEEE Trans Syst Man Cyber 27:153–158

    Article  Google Scholar 

  • Chhibber D, Srivastava PK, Bisht DC (2022) Optimization of a transportation problem under Pythagorean fuzzy environment. J MESA 13(3):769–776

    Google Scholar 

  • Dafermos SC (1972) The traffic assignment problem for multiclass-user transportation networks. Transp Sci 6(1):73–87

    Article  Google Scholar 

  • Ejegwa PA (2020) Distance and similarity measures for Pythagorean fuzzy sets. Granular Comput 5(2):225–238

    Article  MathSciNet  Google Scholar 

  • Evans JR (1979) Aggregation in the generalized transportation problem. Comput Oper Res 6(4):199–204

    Article  Google Scholar 

  • Flood MM (1956) The traveling-salesman problem. Oper Res 4(1):61–75

    Article  MathSciNet  MATH  Google Scholar 

  • Geetha SS, Selvakumari K (2020) A new method for solving Pythagorean fuzzy transportation problem. PalArch’s J Archaeol Egypt/Egyptol 17(7):4825–4834

    Google Scholar 

  • Hong DH, Kim C (1999) A note on similarity measures between vague sets and between elements. Inf Sci 115:83–96

    Article  MathSciNet  MATH  Google Scholar 

  • Hung WL, Yang MS (2004) Similarity measures of intuitionistic fuzzy sets based on Hausdorff distance. Pattern Recognit Lett 25:1603–1611

    Article  Google Scholar 

  • Hussain RJ, Kumar PS (2012) Algorithmic approach for solving intuitionistic fuzzy transportation problem. Appl Math Sci 6(80):3981–3989

    MathSciNet  MATH  Google Scholar 

  • Jeyalakshmi K, Chitra L, Veeramalai G, Krishna Prabha S, Sangeetha S (2021) Pythagorean fuzzy transportation problem via Monalisha technique. Ann RSCB 25(3):2078–2086

    Google Scholar 

  • Krishna PS, Sangeetha S, Hema P, Basheerd M, Veeramalae G (2021) Geometric mean with Pythagorean fuzzy transportation problem. Turk J Comput Math Educ 12(7):1171–1176

    Google Scholar 

  • Kumar R, Edalatpanah SA, Jha S et al (2019) A Pythagorean fuzzy approach to the transportation problem. Complex Intell Syst 5:255–263. https://doi.org/10.1007/s40747-019-0108-1

    Article  Google Scholar 

  • Kundu P, Kar S, Maiti M (2014) Fixed charge transportation problem with type-2 fuzzy variables. Inf Sci 255:170–186

    Article  MathSciNet  MATH  Google Scholar 

  • Li DF, Cheng CT (2002) New similarity measures of intuitionistic fuzzy sets and application to pattern recognitions. Pattern Recognit Lett 23:221–225

    Article  MATH  Google Scholar 

  • Li F, Xu ZY (2001) Measures of similarity between vague sets. J Softw 12:922–927

  • Li Y, Olson DL, Qin Z (2007) Similarity measures between intuitionistic fuzzy (vague) sets: a comparative analysis. Pattern Recognit Lett 28:278–285

    Article  Google Scholar 

  • Liang ZZ, Shi PF (2003) Similarity measures on intuitionistic fuzzy sets. Pattern Recognit Lett 24:2687–2693

    Article  MATH  Google Scholar 

  • Mao Y, Zhong H, Xiao X, Li X (2017) A segment-based trajectory similarity measure in the urban transportation systems. Sensors 17(3):524

    Article  Google Scholar 

  • Mitchell HB (2003) On theDengfeng-Chuntian similarity measure and its application to pattern recognition. Pattern Recognit Lett 24:3101–3104

    Article  Google Scholar 

  • Molodtsov D (1999) Soft set theory-First results. Comput Math Appl 37(4):19–31. https://doi.org/10.1016/S0898-1221(99)00056-5

    Article  MathSciNet  MATH  Google Scholar 

  • Nagar P, Srivastava P. K, Srivastava A (2021). A new dynamic score function approach to optimize a special class of Pythagorean fuzzy transportation problem. Int J Syst Assur Eng Manag 1–10

  • Ngastiti PTB, Surarso B (2018) Zero point and zero suffix methods with robust ranking for solving fully fuzzy transportation problems. J Phys 1022(1):012005

  • Pawlak Z (1982) Rough set. Int J Comput Inform Sci 11(5):341–356. https://doi.org/10.1007/BF01001956

    Article  MATH  Google Scholar 

  • Peng X (2019) New similarity measure and distance measure for Pythagorean fuzzy set. Complex Intell Syst 5:101–111

    Article  Google Scholar 

  • Peng X, Yuan H, Yang Y (2017) Pythagorean fuzzy information measures and their applications. Int J Intell Syst 32:991–1029

    Article  Google Scholar 

  • Pratihar J, Kumar R, Edalatpanah SA (2021) Modified Vogel’s approximation method for transportation problem under uncertain environment. Complex Intell Syst 7:29–40. https://doi.org/10.1007/s40747-020-00153-4

    Article  Google Scholar 

  • Rani D, Gulati TR (2014) Fuzzy optimal solution of interval-valued fuzzy transportation problems. In: Proceedings of the third international conference on soft computing for problem solving, pp 881–888. Springer, New Delhi

  • Ranjan K, Sripati J, Ramayan S (2017) Shortest path problem in network with type-2 triangular Fuzzy arc length. J Appl Res Ind Eng 4(1):1–7

    Google Scholar 

  • Ropke S, Pisinger D (2006) An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows. Transp Sci 40(4):455–472

    Article  Google Scholar 

  • Sahoo L (2021) A new score function based Fermatean fuzzy transportation problem. Results Control Optim 4:100040

    Article  Google Scholar 

  • Sakawa M, Nishizaki I, Uemura Y (2001) Fuzzy programming and profit and cost allocation for a production and transportation problem. Eur J Oper Res 131(1):1–15

    Article  MathSciNet  MATH  Google Scholar 

  • Singh SK, Yadav SP (2016) A new approach for solving intuitionistic fuzzy transportation problem of type-2. Ann Oper Res 243(1):349–363

    Article  MathSciNet  MATH  Google Scholar 

  • Tada M, Ishii H (1996) An integer fuzzy transportation problem. Comput Math Appl 31(9):71–87

    MathSciNet  MATH  Google Scholar 

  • Umamageswari RM, Uthra G (2020) A Pythagorean fuzzy approach to solve transportation problem. Adalya J 9(1):1301–1308

    Google Scholar 

  • Wei G, Wei Y (2018) Similarity measures of Pythagorean fuzzy sets based on the cosine function and their applications. Int J Intell Syst 33(3):634–653

    Article  MathSciNet  Google Scholar 

  • Yager RR (2013). Pythagorean fuzzy subsets. The 9th joint world congress on fuzzy systems and NAFIPS annual meeting. In: IFSA/NAFIPS 2013, pp 57–61. Edmonton, Canada

  • Ye J (2011) Cosine similarity measures for intuitionistic fuzzy sets and their applications. Math Comput Model 53:91–97

    Article  MathSciNet  MATH  Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inform Control 8:338–356. https://doi.org/10.1016/S0019-9958(65)90241-X

    Article  MATH  Google Scholar 

  • Zeng W, Li D, Yin Q (2018) Distance and similarity measures of Pythagorean fuzzy sets and their applications to multiple criteria group decision making. Int J Intell Syst 33(11):2236–2254

    Article  Google Scholar 

  • Zhang X (2016) A novel approach based on similarity measure for Pythagorean fuzzy multiple criteria group decision making. Int J Intell Syst 31:593–611

    Article  Google Scholar 

  • Zhang Q, Hu J, Feng J, Liu A, Li Y (2019) New similarity measures of Pythagorean fuzzy sets and their applications. IEEE Access 7:138192–138202

    Article  Google Scholar 

  • Zhang Q, Hu J, Feng J, Liu A (2020) Multiple criteria decision making method based on the new similarity measures of Pythagorean fuzzy set. J Intell Fuzzy Syst 39(1):809–820

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bornali Saikia.

Ethics declarations

Conflict of interest

The authors declar that there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Saikia, B., Dutta, P. & Talukdar, P. An advanced similarity measure for Pythagorean fuzzy sets and its applications in transportation problem. Artif Intell Rev 56, 12689–12724 (2023). https://doi.org/10.1007/s10462-023-10421-7

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10462-023-10421-7

Keywords

Navigation