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Two novel approaches that reduce the effectiveness of the decision maker in decision making under uncertainty environments | ||
Iranian Journal of Fuzzy Systems | ||
مقاله 9، دوره 19، شماره 2، خرداد و تیر 2022، صفحه 105-117 اصل مقاله (196.47 K) | ||
نوع مقاله: Research Paper | ||
شناسه دیجیتال (DOI): 10.22111/ijfs.2022.6793 | ||
نویسنده | ||
O. Dalkılı¸c* | ||
Department of Mathematics, Mersin University, Mersin, Turkey | ||
چکیده | ||
Unlike other mathematical models, soft set theory provides a parameterization tool contribution. However, in this theory, since membership degrees are expressed as $0$ and $1$, for $(0, 1)$, we cannot determine whether any object belongs to a parameter or not. Researchers have tried to overcome this situation by ensuring that the decision maker expresses these values. However, we cannot know the accuracy of the data provided to us by the decision maker. Therefore, in this study, we introduced the concepts of relational membership function, relational non-membership function, inverse relational membership function and inverse relational non-membership function and examined the related properties of these concepts. Then, we propose two new approaches so that uncertainty can be expressed in an ideal way and can be used in decision-making. Finally, the approaches given and some of the important approaches in the literature are compared and analyzed. | ||
کلیدواژهها | ||
Soft set؛ inverse soft set؛ algorithm؛ decision making | ||
مراجع | ||
[1] M. I. Ali, F. Feng, X. Liu, W. K. Min, M. Shabir, On some new operations in soft set theory, Computers and Mathematics with Applications, 57 (2007), 1547-1553.
[2] M. I. Ali, L. H. Son, I. Deli, N. D. Tien, Bipolar neutrosophic soft sets and applications in decision making, Journal of Intelligent and Fuzzy Systems, 33(6) (2017), 4077-4087.
[3] M. Aslam, S. Abdullah, K. Ullah, Bipolar fuzzy soft sets and its applications in decision making problem, Journal of Intelligent and Fuzzy Systems, 27(2) (2014), 729-742.
[4] K. Atanassov, Intuitionistic fuzzy sets: Theory and applications, Heidelberg, Germany: Physica-Verlag, 1999.
[5] K. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20 (1986), 87-96.
[6] D. G. Chen, E. C. C. Tsang, D. S. Yeung, W. Xizhao, The parameterization reduction of soft sets and its applications, Computers and Mathematics with Applications, 49 (2005), 757-763.
[7] N. Çagman, F. Çıtak, S. Enginoglu, Fuzzy parameterized fuzzy soft set theory and its applications, Turkish Journal of Fuzzy Systems, 1(1) (2010), 21-35.
[8] N. Çagman, S. Enginoglu, Soft set theory and uni-int decision making, European Journal of Operational Research, 207 (2010), 848-855.
[9] N. Çagman, S. Enginoglu, F. Çıtak, Fuzzy soft set theory and its applications, Iranian Journal of Fuzzy Systems, 8(3) (2011), 137-147.
[10] N. Çagman, S. Karatas, Intuitionistic fuzzy soft set theory and its decision making, Journal of Intelligent and Fuzzy Systems, 24(4) (2013), 829-836.
[11] V. Çetkin, A. Aygunoglu, H. Aygun, A new approach in handling soft decision making problems, Journal of Nonlinear Sciences and Applications, 9 (2016), 231-239.
[12] O. Dalkılıç, An application of VFPFSSs in decision making problems, Journal of Polytechnic, (2021), Doi: 10.2339/politeknik.758474.
[13] O. Dalkılıç, N. Demirtas, Bipolar soft filter, Journal of Universal Mathematics, 3(1) (2020), 21-27.
[14] O. Dalkılıç, N. Demirtas, VFP-soft sets and its application on decision making problems, Journal of Polytechnic, (2021), Doi: 10.2339/politeknik.685634.
[15] I. Deli, N. Çagman, Intuitionistic fuzzy parameterized soft set theory and its decision making, Applied Soft Computing, 28 (2015), 109-113.
[16] I. Deli, F. Karaaslan, Bipolar FPSS-theory with applications in decision making, Afrika Matematika, 31(3) (2019), 493-505.
[17] I. Deli, S. Karatas, Interval valued intuitionistic fuzzy parameterized soft set theory and its decision making, Journal of Intelligent and Fuzzy Systems, 30(3) (2016), 2073-2082.
[18] N. Demirtas, O. Dalkılıç, Decompositions of soft α-continuity and soft A-continuity, Journal of New Theory, 31 (2020), 86-94.
[19] N. Demirtas, S. Hussan, O. Dalkılıç, New approaches of inverse soft rough sets and their applications in a decision making problem, Journal of Applied Mathematics and Informatics, 38(3-4) (2020), 335-349.
[20] H. Garg, R. Arora, Maclaurin symmetric mean aggregation operators based on t-norm operations for the dual hesitant fuzzy soft set, Journal of Ambient Intelligence and Humanized Computing, 11(1) (2020), 375-410.
[21] H. Garg, K. Kumar, A novel possibility measure to interval-valued intuitionistic fuzzy set using connection number of set pair analysis and its applications, Neural Computing and Applications, 32(8) (2020), 3337-3348.
[22] K. Hayat, M. I. Ali, F. Karaaslan, B. Y. Cao, M. H. Shah, Design concept evaluation using soft sets based on acceptable and satisfactory levels: An integrated TOPSIS and Shannon entropy, Soft Computing, 24(3) (2020), 2229-2263.
[23] C. Huang, M. Lin, Z. Xu, Pythagorean fuzzy MULTIMOORA method based on distance measure and score function: Its application in multicriteria decision making process, Knowledge and Information Systems, 62(11) (2020), 4373- 4406.
[24] A. M. Irfan, F. Feng, X. Liu, W. K. Minc, M. Shabir, On some new operations in soft set theory, Computers and Mathematics with Applications, 57 (2009), 1547-1553.
[25] Y. Jiang, Y. Tang, Q. Chen, An adjustable approach to intuitionistic fuzzy soft sets based decision making, Applied Mathematical Modelling, 35 (2011), 824-836.
[26] A. M. Khalil, D. Cao, A. A. Azzam, F. Smarandache, W. Alharbi, Combination of the single-valued neutrosophic fuzzy set and the soft set with applications in decisionmaking, Symmetry, 12(8) (2020), 1361.
[27] A. M. Khalil, N. Hassan, Inverse fuzzy soft set and its application in decision making, International Journal of Information and Decision Sciences, 11(1) (2019), 73-92.
[28] M. Kirişçi, Medical decision making with respect to the fuzzy soft sets, Journal of Interdisciplinary Mathematics, 23(4) (2020), 767-776.
[29] Z. Kong, L. Q. Gao, L. F. Wang, S. Li, The normal parameter reduction of soft sets and its algorithm, Computers and Mathematics with Applications, 56 (2008), 3029-3037.
[30] P. S. Kumar, Algorithms for solving the optimization problems using fuzzy and intuitionistic fuzzy set, International Journal of System Assurance Engineering and Management, 11(1) (2020), 189-222.
[31] M. Lin, C. Huang, R. Chen, H. Fujita, X. Wang, Directional correlation coefficient measures for Pythagorean fuzzy sets: Their applications to medical diagnosis and cluster analysis, Complex and Intelligent Systems, 7(2) (2021), 1025-1043.
[32] M. Lin, X. Li, R. Chen, H. Fujita, J. Lin, Picture fuzzy interactional partitioned Heronian mean aggregation operators: An application to MADM process, Artificial Intelligence Review, (2021), 1-38.
[33] P. K. Maji, A. R. Roy, R. Biswas, An application of soft sets in a decision making problem, Computers and Mathematics with Applications, 44 (2002), 1077-1083.
[34] P. K. Maji, A. R. Roy, R. Biswas, Soft set theory, Computers and Mathematics with Applications, 24 (2003), 555-562.
[35] S. Manna, T. M. Basu, S. K. Mondal, A soft set based VIKOR approach for some decision-making problems under complex neutrosophic environment, Engineering Applications of Artificial Intelligence, 89 (2020), 103432, Doi: 10.1016/j.engappai.2019.103432.
[36] A. R. Mishra, A. Mardani, P. Rani, E. K. Zavadskas, A novel EDAS approach on intuitionistic fuzzy set for assessment of health-care waste disposal technology using new parametric divergence measures, Journal of Cleaner Production, 272 (2020), 122807.
[37] D. Molodtsov, Soft set theory-first results, Computers and Mathematics with Applications, 37 (1999), 19-31.
[38] X. Peng, Y. Yang, Algorithms for interval-valued fuzzy soft sets in stochastic multi-criteria decision making based on regret theory and prospect theory with combined weight, Applied Soft Computing, 54 (2017), 415-430.
[39] K. Qin, Z. Hong, On soft equality, Journal of Computational and Applied Mathematics, 234(5) (2010), 1347-1355.
[40] M. Saeed, M. Saqlain, A. Mehmood, K. Naseer, S. Yaqoob, Multi-polar neutrosophic soft sets with application in medical diagnosis and decision-making, Neutrosophic Sets and Systems, 33(1) (2020), 183-207.
[41] P. Suebsan, Inverse int-fuzzy soft bi-ideals over semigroups, Annals of Fuzzy Mathematics and Informatics, 18(1) (2019), 15-30.
[42] N. R. Thi, L. H. Son, M. Ali, D. Tamir, Representing complex intuitionistic fuzzy set by quaternion numbers and applications to decision making, Applied Soft Computing, 87(4) (2020), 105961, Doi:10.1016/j.asoc.2019.105961.
[43] L. A. Zadeh, Fuzzy sets, Information and Control, 8 (1965), 338-353.
[44] X. Zhang, B. Sun, X. Chen, X. Chu, J. Yang, An approach to evaluating sustainable supply chain risk management based on BWM and linguistic value soft set theory, Journal of Intelligent and Fuzzy Systems, 39(3) (2020), 4369- 4382.
[45] R. M. Zulqarnain, X. L. Xin, M. Saeed, N. Ahmed, Application of interval valued fuzzy soft max-min decision making method in medical diagnosis, International Journal of Pharmaceutical Sciences Review and Research, 62(1) (2020), 56-60. | ||
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