Score-Valued Decision Making Models Based on Inverse Soft Matrices

Erdinç, Seda; Aygün, Emin

doi:10.22130/scma.2023.1987342.1234

Articles in Press

Document Type : Research Paper

Authors

Department of Mathematics, Faculty of Science, Erciyes University, Kayseri, Turkey.

https://doi.org/10.22130/scma.2023.1987342.1234

Abstract

In this work, we introduce some useful concepts in soft set theory, such as $\overline{\alpha}$-inverse intersection and $\overline{\alpha}$-inverse union of inverse soft sets, together with the type soft $\overline{\alpha}$-upper, $\overline{\alpha}$-lower, $\overline{\alpha}$-intersection and $\overline{\alpha}$-union of inverse soft matrices. Our main contribution is of proposing a new decision-making method associated with inverse soft sets and inverse soft matrices.

Keywords

Main Subjects

Fuzzy Functional Analysis

References

1. A.M. Khalil and N. Hassan, Inverse fuzzy soft set and its application in decision making, International Journal of Information and Decision Sciences, 11 (2019), pp. 73-92.

2. A.O. Atagün and A. Sezgin, Soft substructures of rings, fields and modules., Comput.Math. Appl., 61 (2011), pp.592-601.

3. A. Sezgin, A.O. Atagün and E. Aygün, A note on soft rings and idealistic soft rings, Filomat, 25 (2011), pp. 53-68.

4. D. Molodtsov, Soft set theory-first results, Comput. Math.Appl., 37 (1999), pp. 19-31.

5. H. Kamacı, K. Saltık, H.F. Akız and A.O. Atagün, Cardinality inverse soft matrix theory and its applications in multicriteria group decision making, J. Intell. Fuzzy Systems, 34 (2018), pp. 2031-2049.

6. H. Kamacı and S.Petchimuthu, The row-products of inverse soft matrices in multicriteria decision making, J. Intell. Fuzzy Systems, 36 (2019 ), pp. 6425-6441

7. K. Qin, J. Yang and X. Zhang, Soft set approaches to decision making problems, in: Proc. 7nd International Conference on Rough Set and Knowledge Technology RSKT, 2012, Chengdu, China, 2012, pp. 456-464.

8. M.I. Ali, F. Feng, X. Liu, W.K. Min and M. Shabir,On some new operations in soft set theory, Comput. Math. Appl., 57(2009), pp. 1547-1553.

9. N. Çağman and I. Deli, Means of FP-soft sets and their Applications., Hacet. J. Math. Stat., 41 (2012), pp. 615-625.

10. N. Çağman and S. Enginoğlu, Soft set theory and uni-int decision making, European J. Oper. Res., 207 (2010), pp. 848-855.

11. N. Çağman and S. Enginouglu, Fuzzy soft matrix theory and its application in decision making, Iran. J. Fuzzy Syst, 9 (1) (2012), pp. 119-109.

12. P.K. Maji, A.R. Roy and Biswas, An application in decision making problem, Comput. Math. Appl., 44 (2002), pp. 1077-1083.

13. P.K Maji, R. Biswas and A.R. Roy, Soft set theory, Comput. Math. Appl., 45 (2003), pp. 555-562.

14. P. Karthick, S.A. Mohiuddine, K. Tamilvanan, S. Narayanamoorthy and S. Maheswari,Investigations of color image segmentation based on connectivity measure, shape priority and normalized fuzzy graph cut, Applied Soft Computing, 139 (2023), pp. 110239

15. V. Çetkin, A. Aygünouğlu and H. Aygün, A new approach in handling soft decision making problems, J. Nonlinear Sci. Appl., 9 (2016), pp. 231-239.

Sahand Communications in Mathematical Analysis

Score-Valued Decision Making Models Based on Inverse Soft Matrices

References

References

Articles in Press, Accepted Manuscript
Available Online from 10 February 2024

Score-Valued Decision Making Models Based on Inverse Soft Matrices

References

References

Articles in Press, Accepted Manuscript Available Online from 10 February 2024

Articles in Press, Accepted Manuscript
Available Online from 10 February 2024