A Soft Interval Based Decision Making Method and Its Computer Application

• Autorzy: Yaylalı Gözde , Polat Nazan Çakmak , Tanay Bekir

Identyfikatory

DOI

10.2478/fcds-2021-0019

• Języki publikacji: EN

Abstrakty

EN

In today’s society, decision making is becoming more important and complicated with increasing and complex data. Decision making by using soft set theory, herein, we firstly report the comparison of soft intervals (SI) as the generalization of interval soft sets (ISS). The results showed that SIs are more effective and more general than the ISSs, for solving decision making problems due to allowing the ranking of parameters. Tabular form of SIs were used to construct a mathematical algorithm to make a decision for problems that involves uncertainties. Since these kinds of problems have huge data, constructing new and effective methods solving these problems and transforming them into the machine learning methods is very important. An important advance of our presented method is being a more general method than the Decision-Making methods based on special situations of soft set theory. The presented method in this study can be used for all of them, while the others can only work in special cases. The structures obtained from the results of soft intervals were subjected to test with examples. The designed algorithm was written in recently used functional programing language C# and applied to the problems that have been published in earlier studies. This is a pioneering study, where this type of mathematical algorithm was converted into a code and applied successfully.

Słowa kluczowe

EN

soft set theory; interval soft set; soft Interval; ordering; soft set; algorithm; decision making

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Foundations of Computing and Decision Sciences
• Rocznik: 2021
• Tom: Vol. 46, No. 3
• Strony: 273--296
• Opis fizyczny: Bibliogr. 24 poz., rys., tab.

Twórcy

autor

Yaylalı Gözde

• Muğla Sıtkı Koçman University Faculty of Science, Department of Mathematics Muğla, Turkey

autor

Polat Nazan Çakmak

• Muğla Sıtkı Koçman University Faculty of Science, Department of Mathematics Muğla, Turkey

autor

Tanay Bekir

• Muğla Sıtkı Koçman University Faculty of Science, Department of Mathematics Muğla, Turkey

Bibliografia

• [1] Babitha K.V. and Sunil J.J. Soft set relations and functions. Comput. Math. Appl., 2010.
• [2] Babitha K.V. and Sunil J.J. Transitive closures and ordering on soft sets. Comput. Math. Appl., 2011.
• [3] Çağman N. and Enginoğlu S. Soft matrix theory and its decision making. Comput. Math. Appl., 2010.
• [4] Das A.K. Weighted fuzzy soft multiset and decision-making. International Journal of Machine Learning and Cybernetics, 2018.
• [5] Khan M.J., Kumam P., Liu P., Kumam W., and Rehman H. An adjustable weighted soft discernibility matrix based on generalized picture fuzzy soft set and its applications in decision making. Journal of Intelligent and Fuzzy Systems, 2020.
• [6] Kirişçi M. ω-soft sets and medical decision-making application. International Journal of Computer Mathematics, 2020.
• [7] Maji P.K., Biswas R., and Roy A.R. Fuzzy soft sets. Journal Fuzzy Mathematics, 2001.
• [8] Maji P.K., Biswas R., and Roy A.R. Soft set theory. Comput. Math. Appl., 2003.
• [9] Maji P.K. and Roy A.R. An application of soft sets in a decision making problem. Comput. Math. Appl., 2002.
• [10] Molodtsov D. Soft set theory-first results. Comput. Math. Appl., 1999.
• [11] Park J.H., Kim O.H., and Kwun Y.C. Some properties of equivalence soft set relations. Comput. Math. Appl., 2012.
• [12] Qamar M.A. and Hassan N. An approach toward a q-neutrosophic soft set and its application in decision making. Symmetry, 2019.
• [13] Sut D.K. An application of fuzzy soft relation in decision making problems. International Journal of Mathematics Trends and Technology, 2012.
• [14] Tanay B. and Yaylalı G. New structures on partially ordered soft sets and soft scott topology. Ann. Fuzzy Math. Inform., 2014.
• [15] Yang H. and Guo Z. Kernels and closures of soft set relations. Comput. Math. Appl, 2011.
• [16] Yao Y.Y. Interval-set algebra for qualitative knowledge representation. In Proceedings of the 5th International Conference on Computing and Information, 1993.
• [17] Yaylalı G., Çakmak Polat N., and Tanay B. Soft intervals and soft ordered topolology. Celal Bayar Univercity Journal of Science, 2017.
• [18] Yaylalı G., Polat N.Ç., and Tanay B. A decision making algorithm on the spft set theory with its computer applications. In International Congress on Fundamental and Applied Sciences 18-22 June 2018 Skope, Macedonia, 2018.
• [19] Zhang H. and Zhan J. Rough soft lattice implication algebras and corresponding decision making methods. International Journal of Machine Learning and Cybernetics, 2017.
• [20] Zhang L. and Zhan J. Fuzzy soft β-covering based fuzzy rough sets and corresponding decision-making applications. International Journal of Machine Learning and Cybernetics, 2019.
• [21] Zhang X. On interval soft sets with applications. International Journal of Computational Intelligence Systems, 2014.
• [22] Zhao H., Ma W., and Sun B. A novel decision making approach based on intuitionistic fuzzy soft sets. International Journal of Machine Learning and Cybernetics, 2017.
• [23] Zhu D., Li Y., Nie H., and Huang C. A decision-making method based on soft set under incomplete information. In 25th Chinese Control and Decision Conference (CCDC), 2013.
• [24] Zhu K. and Zhan J. Fuzzy parameterized fuzzy soft sets and decision making. International Journal of Machine Learning and Cybernetics, 2016.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).