CONFIGURATIONS OF SEVERAL SOFT DECISION-MAKING METHODS TO OPERATE IN FUZZY PARAMETERIZED FUZZY SOFT MATRICES SPACE

Year 2020, Volume: 21 Issue: 1, 58 - 71, 31.03.2020

Serdar Enginoğlu Tutku Öngel

https://doi.org/10.18038/estubtda.562578

Cited By: 6

Abstract

The
concept of fuzzy parameterized fuzzy soft matrices (fpfs-matrices),
which allows for processing fuzzy parameters and fuzzy subsets of the
alternatives by using computers, is a novel and efficient mathematical tool to
cope with uncertainties. Contrary to the methods constructed by fpfs-matrices, the known soft decision-making
(SDM) methods based on soft sets and fuzzy sets cannot model problems whose
parameters and alternatives are fuzzy. Therefore, such methods have been
configured to operate in the fpfs-matrices space. In this paper, we
configure two SDM methods constructed by soft sets, six SDM methods constructed
by fuzzy soft sets, two SDM methods constructed by soft matrices, and four SDM methods
constructed by fuzzy soft matrices. We then apply the configured methods using
one fpfs-matrix as input data to a performance-based value assignment
problem. Finally, we discuss the need for further research.

Keywords

Fuzzy sets, Soft sets, Soft decision-making, Soft matrices, fpfs-matrices

Supporting Institution

Çanakkale Onsekiz Mart University

References

• Molodtsov D. Soft set theory-first results. Comput Math with Appl 1999; 37(4–5): 19–31.
• Maji PK, Biswas R, Roy AR. Soft set theory. Comput Math with Appl 2003; 45(4–5): 555–562.
• Maji PK, Roy AR, Biswas R. An application of soft sets in a decision making problem. Comput Math with Appl 2002; 44(8–9): 1077–1083.
• Çağman N, Enginoğlu S. Soft set theory and uni-int decision making. Eur J Oper Res 2010; 207(2): 848–855.
• Çağman N, Enginoğlu S. Soft matrix theory and its decision making. Comput Math with Appl 2010; 59(10): 3308–3314. Razak SA, Mohamad D. A soft set based group decision making method with criteria weight. Int. Scholarly Sci. Res. Innovation 2011; 5(10): 1641-1646.
• Enginoğlu S, Çağman N, Karataş S, Aydın T. On soft topology. El-Cezeri J Sci Eng 2015; 2(3): 23–38.
• Sezgin A. A new approach to semigroup theory I: Soft union semigroups, ideals and bi-ideals. Algebra Letters 2016; Article ID 3, 46 pages.
• Çıtak F, Çağman N. Soft k-int-ideals of semirings and its algebraic structures. Ann Fuzzy Math Informatics 2017; 13(4): 531–538.
• Şenel G. The relation between soft topological space and soft ditopological space. Commun Fac Sci Univ Ank Ser A1 Math Stat 2018; 67(2): 209–219.
• Karaaslan F. Some properties of AG*-groupoids and AG-bands under SI-product operation. J Intell Fuzzy Syst 2019; 36(1): 231–239.
• Zadeh LA. Fuzzy sets. Inf Control 1965; 8(3): 338–353.
• Maji PK, Biswas R, Roy AR. Fuzzy soft sets. J Fuzzy Math 2001; 9(3): 589–602.
• Çağman N, Çıtak F, Enginoğlu S. Fuzzy parameterized fuzzy soft set theory and its applications. Turkish J Fuzzy Syst 2010; 1(1): 21–35.
• Çağman N, Çıtak F, Enginoğlu S. FP-soft set theory and its applications. Ann Fuzzy Math Inform 2011; 2(2): 219–226.
• Çağman N, Deli İ. Means of FP-soft sets and their applications. Hacettepe J Math Stat 2012; 41(5): 615–625.
• Çağman N, Enginoğlu S. Fuzzy soft matrix theory and its application in decision making. Iran J Fuzzy Syst 2012; 9(1): 109–119.
• Enginoğlu S. Soft matrices. PhD Dissertation, Gaziosmanpaşa University, Tokat, Turkey, 2012.
• Zorlutuna İ, Atmaca S. Fuzzy parametrized fuzzy soft topology. New Trends Math Sci 2016; 4(1): 142–152.
• Riaz M, Hashmi R. Fuzzy parameterized fuzzy soft topology with applications. Ann Fuzzy Math Inform 2017; 13(5): 593–613.
• Riaz M, Hashmi R. Fuzzy parameterized fuzzy soft compact spaces with decision-making, Punjab Univ J Math 2018; 50(2): 131–145.
• Riaz M, Hashmi R, Farooq A. Fuzzy parameterized fuzzy soft metric spaces. J Math Anal 2018; 9(2): 25–36.
• Razak SA, Mohamad DA. Decision making method using fuzzy soft sets. Malaysian J Fundam Appl Sci 2013; 9(2): 99–104.
• Atmaca S, Zorlutuna İ. On topological structures of fuzzy parametrized soft sets. Sci World J 2014, Article ID 164176, 8 pages.
• Deli İ, Çağman N. Relations on FP-soft sets applied to decision making problems. J New Theory 2015; 3: 98–107.
• Enginoğlu E, Çağman N. Fuzzy parameterized fuzzy soft matrices and their application in decision-making. TWMS J Appl Eng Math; In press.
• Enginoğlu S, Memiş S. A configuration of some soft decision-making algorithms via fpfs-matrices. Cumhuriyet Sci J 2018; 39(4): 871–881.
• Enginoğlu S, Memiş S. A review on an application of fuzzy soft set in multicriteria decision making problem [P. K. Das, R. Borgohain, International Journal of Computer Applications 38 (2012) 33–37]. In: Proceedings of The International Conference on Mathematical Studies and Applications 2018; 4–6 October 2018; Karaman, Turkey. pp. 173–178.
• Enginoğlu S, Memiş S. A review on some soft decision-making methods. In: Proceedings of The International Conference on Mathematical Studies and Applications 2018; 4–6 October 2018; Karaman, Turkey. pp. 437–442.
• Enginoğlu S, Memiş S. Comment on fuzzy soft sets [The Journal of Fuzzy Mathematics 9(3), 2001, 589–602]. Int J Latest Eng Res Appl 2018; 3(9): 1–9.
• Enginoğlu S, Memiş S, Arslan B. A fast and simple soft decision-making algorithm EMA18an. In: Proceedings of The International Conference on Mathematical Studies and Applications 2018; 4-6 October 2018; Karaman, Turkey. pp. 428–436.
• Enginoğlu S, Memiş S, Arslan B. Comment (2) on soft set theory and uni-int decision-making [European Journal of Operational Research, (2010) 207, 848–855]. J New Theory 2018; 25: 84–102.
• Enginoğlu S, Memiş S, Öngel T. A fast and simple soft decision-making algorithm EMO18o. In: Proceedings of The International Conference on Mathematical Studies and Applications 2018; 4-6 October 2018; Karaman, Turkey. pp. 179–187.
• Enginoğlu S, Memiş S, Öngel T. Comment on soft set theory and uni-int decision-making [European Journal of Operational Research, (2010) 207, 848–855]. J New Results Sci 2018; 7(3): 28–43.
• Feng F, Jun YB, Liu X, Li L. An adjustable approach to fuzzy soft set based decision making. J Comp Appl Math 2010; 234: 10–20.
• Majumdar P, Samanta SK. On soft mappings. Comput Math with Appl 2010; 60: 2666–2672.
• Çağman N, Enginoğlu S, Çıtak F. Fuzzy soft set theory and its applications. Iran J Fuzzy Syst 2011; 8(3): 137–147. Kalaichelvi A, Malini PH. Application of fuzzy soft sets to investment decision making problem. Int J Math Sci Appl 2011; 1(3): 1583–1586.
• Mou Z. Dynamic multi-evaluation of college foreign language teaching based on fuzzy soft set. Energy Proc 2011; 13: 3183–3188. Yang Y, Ji C. Fuzzy soft matrices and their applications. In: Deng H., Miao D., Lei J., Wang F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science, vol 7002. Springer, Berlin, Heidelberg, pp. 618–627.
• Wu J, Wang Y. A 3PL enterprise customer satisfaction evaluation method based on soft sets. In: IEEE 2011 Seventh International Conference on Natural Computation; pp. 1885–1888.
• Borah MJ, Neog TJ, Sut DK. Fuzzy soft matrix theory and its decision making. Int J Mod Eng Res 2012; 2(2): 121–127.
• Sut DK. An application of fuzzy soft relation in decision making problems. Int J Math Trends and Tech 2012; 3(2): 50–53.
• Mondal JI, Roy TK. Theory of fuzzy soft matrix and its multi criteria in decision making based on three basic t-norm operators. Int J Innovative Res Sci, Eng Tech 2013; 2(10): 5715–5723.
• Nagarajan R, Balamurugan K. Decision making approach for solving fuzzy soft matrix. J Shree Velagapudi Ramakrishna Memorial Coll 2014; 2(3): 23–33.
• Zhang Z. A new method for decision making based on soft matrix theory. J Sci Res Rep 2014; 3(15): 2110–2117.
• Inthumathi V, Chitra V, Jayasree S. The role of operators on soft set in decision making problems. Int J Comput Appl Math 2017; 12(3): 899–910.
• Nagarani S, Kalyani S, Yookesh TL. A soft set approach for selecting the best laptop under fuzzy environment. Int J Comput Math Sci 2017; 6(2): 1–4.
• Chen D, Tsang ECC, Yeung DS, Wang X. The parameterization reduction of soft sets and its applications. Comput Math with Appl 2005; 49: 757–763.
• Kong Z, Gao L, Wang L, Li S. The normal parameter reduction of soft sets and its algorithm. Comput Math with Appl 2008; 56: 3029–3037.
• Erkan U, Gökrem L, Enginoğlu S. Different applied median filter in salt and pepper noise. Comput Electr Eng 2018; 70: 789–798.
• Enginoğlu S, Ay M, Çağman N, Tolun V. Classification of the monolithic columns produced in Troad and Mysia Region ancient granite quarries in Northwestern Anatolia via soft decision-making. Bilge Int J Sci and Tech Res 2019; 3, 21-34.
• Enginoğlu S, Memiş S, Çağman N. A generalisation of fuzzy soft max-min decision-making method and its application to a performance-based value assignment in image denoising. El-Cezerî J Sci Eng 2019; 6(3), 466-481.
• Enginoğlu S, Memiş S, Karaaslan F. A new approach to group decision-making method based on TOPSIS under fuzzy soft environment. J New Results Sci 2019; 8(2), 42-52.
• Memiş S, Enginoğlu S. An application of fuzzy parameterized fuzzy soft matrices in data classification, In: Proceedings of ICONST NST 2019 International Conferences on Science and Technology Natural Science and Technology, 26-30 August 2019, Prizren, Kosovo, pp 68-77.
• Memiş S, Enginoğlu S, Erkan U. A data classification method in machine learning based on normalised hamming pseudo-similarity of fuzzy parameterized fuzzy soft matrices. Bilge Int J Sci and Tech Res 2019; 3, 1-8.