Skip to main content

Numerical Solution to Singularly Perturbed Differential Equation of Reaction-Diffusion Type in MAGDM Problems

  • Conference paper
  • First Online:
Applied Mathematics and Scientific Computing

Part of the book series: Trends in Mathematics ((TM))

Abstract

In multiple attribute group decision-making (MAGDM) problems, weights of decision-makers play a vital role. In this paper, we present a new approach for finding the weights for decision-making process based on singular perturbation problem in which decision-makers’ weights are completely unknown. The attribute weights are derived using the exact and numerical solution for reaction-diffusion type problem. For the decision-making process, we utilize a class of ordered weighted averaging (OWA) operator, and the newly calculated decision-maker weights are used in the computations of identifying the best alternative from the available alternatives. The feasibility of the proposed method is displayed through a numerical illustration, and comparison is made with existing ranking methods.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Atanassov, K. : Intuitionistic fuzzy sets. Fuzzy Sets and Systems. (1986) https://doi.org/10.1016/0165-0114(89)90205-4

    Article  MathSciNet  MATH  Google Scholar 

  2. Atanassov, K. : More on intuitionistic fuzzy sets. Fuzzy Sets and Systems. (1989) https://doi.org/10.1016/0165-0114(89)90215-7

    Article  MathSciNet  MATH  Google Scholar 

  3. Chen, S. M. : Similarity measures between vague sets and between elements. IEEE Trans. Syst. Man Cybern. 27(1), 153–158 (1997)

    Article  Google Scholar 

  4. Chen, S.M., Randyanto, Y. : A Novel Similarity Measure Between Intuitionistic Fuzzy Sets and its Applications. International Journal of Pattern Recognition and Artificial Intelligence. World Scientific Publishing Company. 27(7), 1350021–1350034 (34 pages) (2013)

    Article  Google Scholar 

  5. Hong, D. H., Kim, C. : A note on similarity measures between vague sets and between elements. Inform. Sci. 115(1), 83–96 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  6. Hung, W. L., Yang, M.S. : Similarity measures of intuitionistic fuzzy sets based on Hausdorff distance. Pattern Recogn. Lett. 25(14), 1603–1611 (2004)

    Article  Google Scholar 

  7. Li, D-F., Chuntian, C. : New similarity measures of intuitionistic fuzzy sets and application to pattern recognitions. Pattern Recogn. Lett. 23(13), 221–225 (2002)

    Google Scholar 

  8. Li, D-F., Ye Y-F. : Interval-valued least square prenucleolus of interval-valued cooperative games and a simplified method. Operational Research. 18(1), 205–220 (2018)

    Article  Google Scholar 

  9. Li, D-F., Wan, S-P. : Minimum Weighted Minkowski Distance Power Models for Intuitionistic Fuzzy Madm with Incomplete Weight Information. International Journal of Information Technology and Decision Making. 16(5), 1387–1408 (2017)

    Article  Google Scholar 

  10. Liu, J-C., Li, D-F. : Correlations to TOPSIS-Based Nonlinear-Programming Methodology for Multiattribute Decision making With Interval-Valued Intuitionistic Fuzzy Sets. IEEE Trans. Fuzzy Systems. 26(1), 391 (2018)

    Article  MathSciNet  Google Scholar 

  11. Li, F., Xu, Z. Y. : Measures of similarity between vague sets. J. Software. 12(6), 922–927 (2001)

    Google Scholar 

  12. Li, L., Olson, D.L., Qin, Z. : Similarity measures between intuitionistic fuzzy (vague) sets: A comparative analysis. Pattern Recogn. Lett. 28(2), 278–285 (2007)

    Article  Google Scholar 

  13. Malley, R. E. O. : Introduction to singular perturbations. Academic press New York (1974)

    Google Scholar 

  14. Matthews, S., O’Riordan, E., Shishkin, G.I. : A Numerical Method for a System of Singularly Perturbed Reaction-Diffusion Equations. Journal of Computational and Applied Mathematics. 145(1), 151–166 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  15. Miller, J.J.H., O’Riordan, E., Shishkin, G.I. : Fitted numerical methods for singular perturbation problems. World scientific Publishing Co. Pvt. Ltd. (1996)

    Book  MATH  Google Scholar 

  16. Mitchell, H. B. : On the Li, D-F., Chuntian similarity measure and its application to pattern recognition. Pattern Recogn. Lett. 24(16), 3101–3104 (2003)

    Google Scholar 

  17. Nayfeh, A.H. : Perturbation methods. John Wiley and sons Newyork (1973)

    Google Scholar 

  18. Paramasivam, M., Valarmathi, S., Miller, J.J.H.: Second Order Parameter-Uniform Convergence for a Finite Difference Method for a Singularly Perturbed Linear Reaction-Diffusion System. Math. Commun. 15(2), 587–612 (2010)

    MathSciNet  MATH  Google Scholar 

  19. Robinson, J.P., Amirtharaj, E.C.H. : Contrasting Correlation Coefficient with Distance Measure in Interval Valued Intuitionistic Trapezoidal Fuzzy Numbers. International Journal of Fuzzy System Applications. 5(3), 42–76 (2016)

    Article  Google Scholar 

  20. Robinson, J.P., Jeeva, S. : Mining Trapezoidal Intuitionistic Fuzzy Correlation Rules for Eigen Valued MAGDM Problems. International Journal of Control Theory and Applications. 9(7), 585–616 (2016)

    Google Scholar 

  21. Robinson, J.P., Jeeva, S. : Application of Jacobian & Sor Iteration process in Intuitionistic Fuzzy MAGDM Problems. Mathematical Sciences International Research Journal. 6(2), 130–134 (2017)

    Google Scholar 

  22. Ross, H.G., Stynes, M., Tobiska, L. : Numerical Methods for Singularly Perturbed Differential Equations. Springer-Verlag Newyork (1996)

    Google Scholar 

  23. Yager, R. R., Filev, D. P. : Induced ordered weighted averaging operators. IEEE Transactions on Systems, Man and Cybernetics. 29(1), 141–150 (1999)

    Article  Google Scholar 

  24. Ye, J. : Cosine similarity measures for intuitionistic fuzzy sets and their applications. Math. Comput. Model. 53(1-2), 91–97 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  25. Yu, G-F., Li, D-F. : Application of satisfactory degree to interval-valued intuitionistic fuzzy multi-attribute decision making. Journal of Intelligent and Fuzzy Systems. 32(1), 1019–1028 (2017)

    Article  MATH  Google Scholar 

  26. Yu, G-F., Li., D-F., Qiu, J-M., Zheng X-X. : Some operators of intuitionistic uncertain 2-tuple linguistic variables and application to multi-attribute group decision making with heterogeneous relationship among attributes. Journal of Intelligent and Fuzzy Systems. 34(1), 599–611 (2018)

    Article  Google Scholar 

  27. Zadeh, L. A. : Fuzzy Sets. Information and Control. 8(3), 338–356 (1965)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Robinson, P.J., Indhumathi, M., Manjumari, M. (2019). Numerical Solution to Singularly Perturbed Differential Equation of Reaction-Diffusion Type in MAGDM Problems. In: Rushi Kumar, B., Sivaraj, R., Prasad, B., Nalliah, M., Reddy, A. (eds) Applied Mathematics and Scientific Computing. Trends in Mathematics. Birkhäuser, Cham. https://doi.org/10.1007/978-3-030-01123-9_1

Download citation

Publish with us

Policies and ethics