INDEXED IN 

International Journal of Modern Science and Technology

ISSN 2456-0235

International Journal of Modern Science and Technology, 1(5), 2016, Pages 159-163. 


Interval-Valued Product Fuzzy Soft Matrices and its Application in Decision Making

S. Vijayabalaji*, N. Sathiyaseelan
*Department of Mathematics,University College of Engineering, Panruti-60710, Tamilnadu, India.

Abstract
Matrix theory plays a significant role in decision making situation. The study of matrices in fuzzy setting has always attracted researchers to a greater extend. Fuzzy matrix is a matrix over fuzzy algebra. Soft set is another interesting theory on uncertainty. Cagman made effort in defining soft matrices and fuzzy soft matrices. Interval-valued fuzzy set is another generalization of fuzzy sets that was introduced by Zadeh. Motivated by the theory of soft sets, soft matrices and product fuzzy soft matrices our aim in this paper is to introduce the notion of interval-valued product fuzzy soft matrices as a generalization of product fuzzy soft matrices. We also provide an interesting decision theory on it. 

​​Keywords: ​Qualitative analysis; Mathematical model; Biological control; Cereal aphid; Population dynamics. 

References

  1. Zadeh LA. Fuzzy sets. Information and Control 8 (1965) 338-353.
  2. Zadeh LA. The concept of a linguistic variable and its application to approximate reasoning. Information and Control 8 (1975) 199-249.
  3. Molodstov DA. Soft set theory - First results. Computers and Mathematics with Applications 37 (1999) 19-31.
  4. Maji PK, Biswas R, Roy AR. Soft set theory. Computers and Mathematics with Applications 45(2003) 555-562.
  5. Maji PK, Roy AR. An Application of soft set in decision making problem. Computers and Mathematics with Applications. 44 (2002) 1077-1083.
  6. Maji PK. Roy AR. A fuzzy soft set theoretic approach to decision making problem. Journal of computational and Applied Mathematics 203 (2007) 412-418.
  7. Cagman N, Enginoglu S. Soft set theory and uni-int decision making. European Journal of Operational Research 207 (2010) 848-855.
  8. Cagman N, Enginoglu S. Soft matrix theory and its decision making. Computers and Mathematics with Applications. 59 (2010) 3308-3314.
  9. Aktas H, Cagman N. Soft sets and soft groups. Information Sciences 177) (2007) 2726-2735.
  10. Ali MI, Feng F, Liu X, Min WK, Shabir M. On some new operations in soft set theory. Computers and Mathematics with Applications 57 (2009) 1547-1553.
  11. Cagman N, Enginogul S, Citak F. Fuzzy soft set theory and its application. Iranian Journal of Fuzzy Systems 8 (2011) 137-147.
  12. Jon Arockiaraj J, Sathiyaseelan N. An application of fuzzy soft set based student ranking system. International Journal of computing Algorithm 3 (2014) 745-748.
  13. Thomason MG. Convergence of power of a fuzzy matrix. Journal of Mathematical Analysis and Application 57 (1977) 476-480.
  14. Vijayabalaji S, Ramesh A. A new decision making theory in soft matrices. International Journal of pure and Applied Mathematics 86 (2013) 927-939.
  15. Vijayabalaji S, Shyamsundar G, Ramesh A. A new decision making theory in product fuzzy soft matrices. Proceedings of the International Conference on Mathematics and its Application (2014) 578-593.
  16. Maji PK, Biswas R, Roy AR. Fuzzy soft sets. Journal of Fuzzy Mathematics. 9 (2001) 589-602.
  17. Mitra Basu T, Kumar Mahapatra N, Kumar Mondal S. Matrices in interval-valued fuzzy soft set theory and their application. South Asian Journal of Mathematics. 4 (2014) 1-22.
  18. Pal M, Kahan SK, Shyamal AK. Intuitionistic fuzzy matrices. Notes on Intuitionistic Fuzzy Sets. 8 (2002)51-62.
  19. Pal M, Kahan SK. Interval-valued intuitionistic fuzzy matrices. Notes on Intuitionistic Fuzzy Sets 11(2005) 16-27.