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Introducing and solving the hesitant fuzzy system AX = B

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper the solution for hesitant fuzzy system as AX = B is introduced where A is an n×n known hesitant fuzzy matrix, B is an n×1 known hesitant fuzzy vector and X is an n×1 unknown hesitant fuzzy vector. First, L-norm and L1-norm of a hesitant fuzzy vector are introduced. Then, the concepts of hesitant fuzzy zero, ’almost equal’ and ’less than’ and ’equal’ are defined for two hesitant fuzzy numbers. Finally, using a minimization problem; the hesitant fuzzy system is solved. At the end, some numerical examples are presented to show the effectiveness of the proposed method.
Rocznik
Strony
553--574
Opis fizyczny
Bibliogr. 25 poz., rys.
Twórcy
  • Department of Mathematics and Statistics, Gonbad Kavous University, Gonbad Kavous, Iran
  • Faculty of Engineering and Natural Science, Istinye University, Istanbul, Turkey
Bibliografia
  • Alcantud, J. C. R. and Torra, V. (2018) Decomposition theorems and extension principles for hesitant fuzzy sets. Information Fusion, 41, 48-56.
  • Allahviranloo, T. and Babakordi, F. (2017) Algebraic solution of fuzzy linear system as: $$\widetilde {A}\widetilde {X}+\widetilde {B}\widetilde {X}= \widetilde {Y}$$ A˜X˜+ B˜X˜= Y˜.Soft Computing, 21, 24, 7463-7472.
  • Anitha, K. and Venkatesan, P. (2016) Properties Of Hesitant Fuzzy Sets. Global Journal of Pure and Applied Mathematics (GJPAM).12,1, 114-116.
  • Babakordi, F. (2020a) A Novel Transformation Method for Solving Complex Interval Matrix. International Journal of Industrial Mathematics, 12, 3, 239–244.
  • Babakordi, F. (2020b) Hesitant fuzzy set and its types. Decisions and Operations Research, 4, 4, 353-361.
  • Babakordi, F., Allahviranloo, T.and Adabitabarrozja, M. (2016) An efficient method for solving LR fuzzy dual matrix system. Journal of Intelligent & Fuzzy Systems, 30, 575–581.
  • Babakordi, F. and Taghinezhad, N. A. (2021) Introducing hesitant fuzzy equations and determining market equilibrium price. Control and Cybernetics, 50, 3.
  • Buckley, J. (1991) Solving fuzzy equations: a new solution concept. Fuzzy Sets Syst, 39, 3, 291–301.
  • Farhadnia, B. (2014) A series of score function for hesitant fuzzy sets. Inf. Sci., 277, 102-110.
  • Lalotra, S. and Singh, S. (2020) Knowledge measure of hesitant fuzzy set and its application in multi-attribute decision-making. Computational and Applied Mathematics, 39, 2, 31 pages.
  • Lan, J., Jin, R., Zheng, Z. and Hu, M. (2017) Priority degrees for hesitant fuzzy sets: Application to multiple attribute decision making, Operations Research Perspectives, 4, 67-73.
  • Meng, F.-y.,Tang, J. and Pedrycz, W. (2021) Dual hesitant fuzzy decision making in optimization models. Computers & Industrial Engineering, 154, 107103.
  • Nasseri, S. H., Khalili, F., Taghi-Nezhad, N. and Mortezania, S. (2014) A novel approach for solving fully fuzzy linear programming problems using membership function concepts. Ann. Fuzzy Math. Inform, 7, 3, 355-368.
  • Rodriguez, R. M., Xu, Z. and Martinez, L. (2018) Hesitant Fuzzy Information for Information Fusion in Decision Making. Information Fusion, 42, 62-63.
  • Sindhu, M. S., Rashid, T., Kashif, A. and Guirao, J. L. G. (2019) Multiple Criteria Decision Making Based on Probabilistic Interval-Valued Hesitant Fuzzy Sets by Using LP Methodology. Discrete Dynamics in Nature and Society, Article ID 1527612, 12 pages.
  • Taghi-Nezhad, N. (2019) The p-median problem in fuzzy environment: proving fuzzy vertex optimality theorem and its application. Soft Computing, 23, 11399-11407.
  • Taleshian, F., Fathali, J. and Taghi-Nezhad, N. A. (2018) Fuzzy majority algorithms for the 1-median and 2-median problems on a fuzzy tree. Fuzzy Information and Engineering, 10, 5, 1-24.
  • Torra, V. (2010) Hesitant fuzzy sets. International Journal of Intelligent Systems, 25, 6, 529-539.
  • Torra, V. and Narukawa, Y. (2009) On hesitant fuzzy sets and decision, The 18th IEEE International Conference on Fuzzy Systems, Jeju Island, Korea, 1378–1382.
  • Wang, F., Li, X. and Chen, X. (2014) Hesitant Fuzzy Soft Set and Its Applications in Multicriteria Decision Making. Journal of Applied Mathematics, Article ID 643785, 10 pages.
  • Xia, M.M. and Xu, Z.S. (2011) Hesitant Fuzzy Aggregation In Decision Making. International Journal of Approximate Reasoning, 52, 3, 395-407.
  • Xiao, J., Cai, J. and Wang, X. (2017) A Hesitant Fuzzy Linguistic Multicriteria Decision-Making Method with Interactive Criteria and Its Application to Renewable Energy Projects Selection. Mathematical Problems in Engineering, Article ID 9634725, 15 pages.
  • Xu, Z. S. (2015) Hesitant Fuzzy Sets Theory. Spriger-Verlag, Berlin.
  • Xu, Z. S. and Xia, M. M. (2011) Distance and similarity measures for hesitant fuzzy sets. Inf. Sci., 181, 2128-2138.
  • Zhu, B. and Xu, Z. (2018) Probability-Hesitant Fuzzy Sets And The Representation Of Preference Relations. Technological and Economic Development of Economy, 24, 3, 1029–1040.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-560a9b30-3a6d-4a91-b316-83e84e7abfa0
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