An Application of Soft Set and Fuzzy Soft Set Theories to Stock Management

Year 2017, Volume: 21 Issue: 3, 791 - 796, 14.09.2017

Nihal Taş Nihal Yılmaz Özgür Pelin Demir

https://doi.org/10.19113/sdufbed.82887

Cited By: 11

Abstract

We give a new application of both notions of a soft set and of a fuzzy soft set to the effective management of stock-out situation. We construct a model to track the remaining raw materials in stock at the end of the first week (or first month) by using soft sets theory. Then we introduce an algorithm for factors influencing stock management using the notion of a fuzzy soft set. If we use these soft set and fuzzy soft set models at the same time, we can more accurately track the stock-out situations of raw materials.

Keywords

Soft set, Fuzzy soft set; Stock management; Stock-out situation

References

• [1] Chaudhuri, A., De, Dr. K., Chatterjee, Dr. D. 2009. Solution of the decision making problems using fuzzy soft relations. International Journal of Information Technology, 15 (1), 29 pages.
• [2] Chou, C. C., Yih, J. M., Ding, J. F., Han, T. C., Lin, Y. H., Liu, L. J., Hsu, W. K. 2012. Application of a fuzzy EOQ model to the stock management in the manufacture system. Key Engineering Materials, 499, 361-365.
• [3] Eksin, C., Güzelkaya, M., Ye¸sil, E., Eksin, ˙I. 2008. Fuzzy logic approach to mimic decision making behavior of humans in stock management game. Proceedings of the 2008 System Dynamics Conference.
• [4] Han, B. 2016. Comments on “Normal parameter reduction in soft set based on particle swarm optimization algorithm”. Appl. Math. Model., http://dx.doi.org/10.1016/j.apm.2016.06.004
• [5] Kalaichelvi, Dr. A., Malini, P. H. 2011. Application of fuzzy soft sets to investment decision making problem. International Journal of Mathematical Sciences and Applications, 1 (3), 583-1586.
• [6] Kong, Z., Wang, L., Wu, Z. 2011. Application of fuzzy soft set in decision making problems based on grey theory. J. Comput. Appl. Math., 236, 1521-1530.
• [7] Kong, Z., Jia, W., Zhang, G., Wang, L. 2015. Normal parameter reduction in soft set based on particle swarm optimization algorithm. Appl. Math. Model., 39, 4808-4820 .
• [8] Maji, P. K., Biswas, R., Roy, A. R. 2001. Fuzzy soft sets. J. Fuzzy Math., 9, 589-602.
• [9] Maji, P. K., Biswas, R., Roy, A. R. 2003. Soft set theory. Comput. Math. Appl., 45, 555-562.
• [10] Molodtsov, D. 1999. Soft set theory - first results. Comput Math. Appl., 37, 19-31.
• [11] Özgür, N. Y., Ta¸s, N. 2015. A note on "application of fuzzy soft sets to investment decision making problem". Journal of New Theory, 1 (7), 1-10.
• [12] Yüksel, ¸S., Dizman, T., Yıldızdan, G., Sert, Ü. 2013. Application of soft sets to diagnose the prostate cancer risk. J Inequal Appl., doi:10.1186/1029-242X-2013-229
• [13] Yüksel, ¸S., Tozlu, N., Dizman, T. 2015. An application of multicriteria group decision making by soft covering based rough sets. Filomat, 29 (1), 209-219.
• [14] Matlab R2015a and Curve Fitting Toolbox (Version 8.5), The Mathworks, Inc., Natick, Massachusetts, United States (2015).