Research Article

A Fuzzy Numerical Simulation-based Heuristic Method for Fully Fuzzy Systems of Linear Equations

Volume: 13 Number: 4 December 15, 2023
TR EN

A Fuzzy Numerical Simulation-based Heuristic Method for Fully Fuzzy Systems of Linear Equations

Abstract

In this paper, a new method is proposed to find the approximate solutions to fully fuzzy systems of linear equations (FFSLEs). The technique integrates a bisection method with Fuzzy Numerical Simulation (FNS). The procedure starts with generating single values of fuzzy parameters and solving the resulting crisp problems repeatedly to determine the lower and upper bounds of the solutions. After computing the mean lower and upper bound values, the obtained supremum and infimum values are considered to be the lower and upper bounds of the solutions, respectively. It is attempted to improve solutions by considering an error function related to the sum of the absolute differences between the corresponding lower and upper bounds of the left and right sides of the equalities. When very large intervals are obtained for the solutions, the bisection algorithm is applied to reduce the error value. The method intends to solve square systems of large dimensions for arbitrary fuzzy numbers (FNs) by removing non-negativity confinements of the variables and/or coefficients to be more realistic. After the computational method is presented thoroughly, some benchmark examples are finally provided.

Keywords

Approximate solution, Bisection method, Fully fuzzy systems of linear equations, Fuzzy numerical simulation

References

  1. Ahlatcioglu, M., Albayrak, I., Kocken, H. G., and Ozkok, B. A. (2016). A mixed integer programming approach to a square fully fuzzy linear equation. Journal of Intelligent and Fuzzy Systems, 31(3), 2009-2015. https://doi.org/10.3233/JIFS-16227
  2. Akdemir, H. G. (2023). Approximate Fuzzy Inverse Matrix Calculation Method using Scenario-based Inverses and Bisection. Fundamental Journal of Mathematics and Applications, 6(1), 42-50. https://doi.org/10.33401/fujma.1195121
  3. Akdemir, H. G., and Kocken, H. G. (2022). A new fuzzy linear regression algorithm based on the simulation of fuzzy samples and an application on popularity prediction of Covid-19 related videos. Journal of Statistics and Management Systems, 1 17. https://doi.org/10.1080/09720510.2021.2016988
  4. Albayrak, I. (2017). On fuzzy solutions of the nonsquare fully fuzzy linear equation system with arbitrary triangular fuzzy numbers. Journal of Intelligent and Fuzzy Systems, 33(6), 3929-3938. https://doi.org/10.3233/JIFS-17774
  5. Allahviranloo, T., Hosseinzadeh, A. A., Ghanbari, M., Haghi, E., and Nuraei, R. (2014). On the new solutions for a fully fuzzy linear system. Soft Computing, 18, 95-107. https://doi.org/10.1007/s00500-013-1037-3
  6. Allahviranloo, T., Kiani, N. A., Barkhordary, M., and Mosleh, M. (2008). Homomorphic solution of fully fuzzy linear systems. Computational Mathematics and Modeling, 19, 282-291. https://doi.org/10.1007/s10598-008-9004-z
  7. Allahviranloo, T., and Mikaeilvand N. (2011). Non zero solutions of the fully fuzzy linear systems. Applied and Computational Mathematics, 10(2), 271-282.
  8. Allahviranloo, T., Salahshour, S., Homayoun-Nejad, M., and Baleanu, D. (2013, January). General solutions of fully fuzzy linear systems. In Abstract and Applied Analysis (Vol. 2013). Hindawi. https://doi.org/10.1155/2013/593274
  9. Allahviranloo, T., Salahshour, S., and Khezerloo, M. (2011). Maximal-and minimal symmetric solutions of fully fuzzy linear systems. Journal of Computational and Applied Mathematics, 235(16), 4652-4662. https://doi.org/10.1016/j.cam.2010.05.009
  10. Babbar, N., Kumar, A., and Bansal, A. (2013a). Linear programming approach to find the solution of fully fuzzy linear systems with arbitrary fuzzy coefficients. Journal of Intelligent and Fuzzy Systems, 25(3), 747-753. https://doi.org/10.3233/IFS-120681
APA
Günay Akdemir, H. (2023). A Fuzzy Numerical Simulation-based Heuristic Method for Fully Fuzzy Systems of Linear Equations. Karadeniz Fen Bilimleri Dergisi, 13(4), 1361-1376. https://doi.org/10.31466/kfbd.1275692
AMA
1.Günay Akdemir H. A Fuzzy Numerical Simulation-based Heuristic Method for Fully Fuzzy Systems of Linear Equations. KFBD. 2023;13(4):1361-1376. doi:10.31466/kfbd.1275692
Chicago
Günay Akdemir, Hande. 2023. “A Fuzzy Numerical Simulation-Based Heuristic Method for Fully Fuzzy Systems of Linear Equations”. Karadeniz Fen Bilimleri Dergisi 13 (4): 1361-76. https://doi.org/10.31466/kfbd.1275692.
EndNote
Günay Akdemir H (December 1, 2023) A Fuzzy Numerical Simulation-based Heuristic Method for Fully Fuzzy Systems of Linear Equations. Karadeniz Fen Bilimleri Dergisi 13 4 1361–1376.
IEEE
[1]H. Günay Akdemir, “A Fuzzy Numerical Simulation-based Heuristic Method for Fully Fuzzy Systems of Linear Equations”, KFBD, vol. 13, no. 4, pp. 1361–1376, Dec. 2023, doi: 10.31466/kfbd.1275692.
ISNAD
Günay Akdemir, Hande. “A Fuzzy Numerical Simulation-Based Heuristic Method for Fully Fuzzy Systems of Linear Equations”. Karadeniz Fen Bilimleri Dergisi 13/4 (December 1, 2023): 1361-1376. https://doi.org/10.31466/kfbd.1275692.
JAMA
1.Günay Akdemir H. A Fuzzy Numerical Simulation-based Heuristic Method for Fully Fuzzy Systems of Linear Equations. KFBD. 2023;13:1361–1376.
MLA
Günay Akdemir, Hande. “A Fuzzy Numerical Simulation-Based Heuristic Method for Fully Fuzzy Systems of Linear Equations”. Karadeniz Fen Bilimleri Dergisi, vol. 13, no. 4, Dec. 2023, pp. 1361-76, doi:10.31466/kfbd.1275692.
Vancouver
1.Hande Günay Akdemir. A Fuzzy Numerical Simulation-based Heuristic Method for Fully Fuzzy Systems of Linear Equations. KFBD. 2023 Dec. 1;13(4):1361-76. doi:10.31466/kfbd.1275692