A new decision making approach for winning strategy based on muti soft set logic

Document Type: Research Paper


1 Department of Mathematics, Central University of Tamil Nadu Thiruvarur.

2 Department of Mathematics, Sri Kaliswari College, Sivakasi.


We introduce a new concept of certainty and coverage of a parameter of the soft set and present a new decision making approach for the soft set over the universe using the certainty of a parameter. Also, we point out the drawbacks of the reduct definition by pointing out the delusion of Proposition 14 given by Herawan et al. [20] and provide the revised definition of the reduct of the multi soft set.


Main Subjects

[1] Zadeh, L. A. (1965). Fuzzy Set. Information and control, 8, 338 - 353.
[2] Pawlak, Z. (1982).  Rough sets. Int. J. Comput. Inform. Sci., 11, 341 - 356.
[3] Molodtsov, D. (1999).  Soft set theory - First results. Comput. Math. Appl., 37, 19 - 31.
[4] Maji, P. K., Biswas, R. & Roy, A. R. (2003). Soft set theory. Comput. Math. Appl., 45, 555 - 562.
[5] Maji, P. K. & Roy, A. R. (2002). An application of soft sets in a decision making problem. Comput. Math. Appl., 44, 1077 - 1083.
[6] Maji, P. K. & Roy, A. R. (2007). A fuzzy soft set theoretic approach to decision making problems. J. Comput. Appl. Math., 203, 412 - 418.
 [7] Cagman, N. & Enginoglu, S. (2010). Soft set theory and uni-int decision making. Eur. J. Oper. Res., 207, 848 - 855.
[8] Cagman, N. & Enginoglu, S. (2010). Soft matrix theory and its decision making. Comp. Math.    Appl., 59, 3308 - 3314.
 [9] Feng, F., Li. Y.  & Cagman, N. (2012). Generalized uni-int decision making schemes based on choice value soft sets. Eur. J. Oper. Res., 220, 162 - 170.
[10] Han, B. & Geng, S. (2013). Pruning method for optimal solutions of  decision making scheme. Eur. J. Oper. Res., 231, 779 - 783.
[11] Feng, Q. & Zhou, Y. (2014). Soft discernibility matrix and its applications in decision making. Appl. Soft Comp., 24, 749 - 756.
[12] Dauda, M. K., Mamat, M. & Waziri, M. Y. (2015). An application of soft set in decision making. Jurnal Teknologi (sciences and engineering), 77(13), 119 - 122.
[13] Wang, X., Xu, Z. & Gou, X. (2020). A novel plausible reasoning based on intuitionistic fuzzy propositional logic and its application in decision making. Fuzzy Optim Decis making, 19, 251–274. https://doi.org/10.1007/s10700-020-09319-8.
[14] Meng, X., Gong, L. & Yao, J. (2020). A fuzzy evaluation approach with the quasi-ordered set: evaluating the efficiency of decision making units. Fuzzy Optim Decis making, 19, 297–310.  https://doi.org/10.1007/s10700-020-09321-0 
[15] Baraka, S., & Dahooei, J. H. (2018). A novel hybrid fuzzy DEA-Fuzzy MADM method for airlines safety evaluation. Journal of air transport management73, 134–149.
[16] Mehlawat, M. K., Kumar, A., Yadav, S., & Chen, W. (2018). Data envelopment analysis based fuzzy multi-objective portfolio selection model involving higher moments. Information sciences460, 128–150.
[17] Meng, X. L., Shi, F. G., & Yao, J. C. (2018). An inequality approach for evaluating decision making units with a fuzzy output. Journal of intelligent and fuzzy systems34, 459–465. 
[18] Meng, X. L., Gong, L. T., & Yao, J. C. (2019). A fuzzy inequality evaluation approach for measuring the relative efficiency. Journal of intelligent and fuzzy systems37, 6589–6600.
[19] Herawan, T., & Deris, M. M. (2009, September). On multi-soft sets construction in information systems. International conference on intelligent computing (pp. 101-110). Springer, Berlin, Heidelberg.
 [20] Herawan, T., Deris, M. M., & Abawajy, J. H. (2010, March). Matrices representation of multi soft-sets and its application. International conference on computational science and its applications (pp. 201-214). Springer, Berlin, Heidelberg.