Averaging aggregation operators with pythagorean trapezoidal fuzzy numbers and their application to group decision making

Journal of Intelligent & Fuzzy Systems - Tập 36 Số 2 - Trang 1899-1915 - 2019
Muhammad Shakeel1, S. Abduulah2, Muhammad Shahzad1, Tariq Mahmood3, Nasir Siddiqui4
1Department of Mathematics, Hazara University, Mansehra, KPK, Pakistan
2Department of Mathematics, Abdul Wali Khan University Mardan KPK, Pakistan
3Department of Electronics Engineering, University of Engineering and Technology Taxila Sub Campus, Chakwal, Pakistan
4Department of Basic Sciences, University of Engineering and Technology, Taxila, Pakistan

Tóm tắt

Từ khóa


Tài liệu tham khảo

Atanassov K.T. , More on intuitionistic fuzzy sets Fuzzy sets and systems, 33(1) (1989), 37–45.

Zadeh, 1965, Fuzzy sets, Inform Control, 8, 338, 10.1016/S0019-9958(65)90241-X

Atanassov, 1996, An equality between intuitionistic fuzzy sets, Fuzzy Sets and Systems, 79, 257, 10.1016/0165-0114(95)00173-5

Li, 2011, Closeness coefficient based nonlinear programming method for interval-valued intuitionistic fuzzy multiattribute decision making with incomplete preference information, Appl Soft Comput, 11, 3042, 10.1016/j.asoc.2011.01.011

Wan, 2013, Fuzzy linmap approach to heterogeneous MADM considering comons of alternatives with hesitation degrees, Omega, 41, 925, 10.1016/j.omega.2012.12.002

Szmidt E. and Kacprzyk J. , Intuitionistic fuzzy sets in some medical applications, in Computational Intelligence. Theory and Applications, Springer, pp, (2001), 148–151.

Shakeel, 2017, Induced averaging aggregation operators with interval pythagorean trapezoidal fuzzy numbers and their application to group decision making, The Nucleus, 2, 140

Wang, 2008, Overview on fuzzy multi-criteria decision making approach, Control Decision, 23, 601

Wang, 2009, Multi-criteria decision-making method with incomplete certain information based on intuitionistic fuzzy number, Control Decision, 24, 226

Wei, 2010, Some induced geometric aggregation operators with intuitionistic fuzzy information and their application to group decision making, Appl Soft Comput, 10, 423, 10.1016/j.asoc.2009.08.009

Yager R.R. , Pythagorean fuzzy subsets. In Edmonton, Proc Joint IFSA World Congress and NAFIPS Annual Meeting Canada, (2013), pp, 57–61.

Xu, 2005, An overview of methods for determining owa weights, Int J Intell Syst, 20, 843, 10.1002/int.20097

Atanassov, 1994, New operations defined over the intuitionistic fuzzy sets, Fuzzy Sets Syst, 137, 10.1016/0165-0114(94)90229-1

De, 2001, An application of intuitionistic fuzzy sets in medical diagnosis, Fuzzy Sets and Systems, 117, 209, 10.1016/S0165-0114(98)00235-8

Chen, 2011, A new multiple attribute group decision making method in intuitionistic fuzzy setting, Applied Mathematical Modelling, 35, 4424, 10.1016/j.apm.2011.03.015

Kharal, 2009, Homeopathic drug selection using intuitionistic fuzzy sets, Homeopathy, 98, 35, 10.1016/j.homp.2008.10.003

Xu, 2006, Some geometric aggregation operators based on intuitionistic fuzzy sets, Int J Gen Syst, 417, 10.1080/03081070600574353

Xu, 2008, Dynamic intuitionistic fuzzy multi-attribute decision making, Int J Approx Reason, 246, 10.1016/j.ijar.2007.08.008

Ma, 2016, Symmetric pythagorean fuzzy weighted geometric/averaging operators and their application in multicriteria decision-making problems, International Journal of Intelligent Systems, 1

Zhang, 2014, Extension of TOPSIS to multiple criteria decision making with pythagorean fuzzy sets, International Journal of Intelligent Systems, 29, 1061, 10.1002/int.21676

Yager, 2014, Pythagorean membership grades in multi-criteria decision making, IEEE Trans Fuzzy Syst, 22, 958, 10.1109/TFUZZ.2013.2278989

Garg, 2017, A novel improved accuracy function for interval valued Pythagorean fuzzy sets and its applications in decision making process, International Journal of Intelligent Systems, Wiley, 32, 1247, 10.1002/int.21898

Garg, 2017, Confidence levels based Pythagorean fuzzy aggregation operators and its application to decision-making process, Computational and Mathematical Organization Theory, 23, 546, 10.1007/s10588-017-9242-8

Kumar, 2016, TOPSIS method based on the connection number of set pair analysis under interval-valued intuitionistic fuzzy set environment, Computational and Applied Mathematics, 1

Garg, 2018, A linear programming method based on an improved score function for interval-valued Pythagorean fuzzy numbers and its application to decision-making, International Journal of Uncertainties, Fuzziness and Knowledge-Based Systems, 26, 67, 10.1142/S0218488518500046

Garg, 2017, Generalized Pythagorean fuzzy Geometric aggregation operators using Einstein t-norm and t-conorm for multicriteria decision-making process, Intenational Journal of Intelligent Systems, Wiley, 32, 597, 10.1002/int.21860

Garg, 2016, A novel correlation coefficients between Pythagorean fuzzy sets and its applications to decision-making processes, International Journal of Intelligent Systems, Wiley, 31, 1234, 10.1002/int.21827

Garg, 2016, A novel accuracy function under interval-valued Pythagorean fuzzy environment for solving multicriteria decision making problem, Journal of Intelligent and Fuzzy Systems, 31, 529, 10.3233/IFS-162165

Garg, 2016, A new generalized improved score function of interval-valued intuitionistic fuzzy sets and applications in expert systems, Applied Soft Computing, Elsevier, 38, 989

Garg, 2016, Generalized intuitionistic fuzzy interactive geometric interaction operators using Einstein t-norm and t-conorm and their application to decision making, Computer and Industrial Engineering, Elsevier, 101, 53, 10.1016/j.cie.2016.08.017

Garg, 2017, Novel intuitionistic fuzzy decision making method based on an improved operation laws and its application, Engineering Applications of Artificial Intelligence, Elsevier, 60, 164, 10.1016/j.engappai.2017.02.008

Gou, 2016, The properties of continuous pythagorean fuzzy information, International Journal of Intelligent Systems, 31, 401, 10.1002/int.21788

Liu, 2016, Generalized ordered modular averaging operator and its application to group decision making,&, Systems, 299, 1

Huayou Chen, 2014, On the properties of the generalized OWHA operators and their application to group decision making, Journal of Intelligent and Fuzzy Systems, 27, 2077, 10.3233/IFS-141173

Liu, 2015, Generalized linguistic ordered weighted hybrid logarithm averaging operators and applications to group decision making, International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, 23, 421, 10.1142/s021848851550018x

Liu, 2013, The continuous Quasi-OWA operator and its application to group decision making, Group Decision and Negotiation, 22, 715, 10.1007/s10726-012-9288-4

He, 2015, Hesitant fuzzy power bonferroni means and their application to multiple attribute decision making, IEEE Transactions on Fuzzy Systems, 23, 1655, 10.1109/TFUZZ.2014.2372074

He, 2016, Extensions of Atanassov’s intuitionistic fuzzy interaction Bonferroni means and Their Application to Multiple attribute decision making, IEEE Transactions on Fuzzy Systems, 24, 558, 10.1109/TFUZZ.2015.2460750

He, 2017, Robust fuzzy programming method for MRO problems considering location effect, dispersion effect and model uncertainty, Computers and Industrial Engineering, 105, 76, 10.1016/j.cie.2016.12.021

He, 2015, Intuitionistic fuzzy interaction bonferroni means and its application to multiple attribute decision making, IEEE Transactions on Cybernetics, 45, 116, 10.1109/TCYB.2014.2320910

Ban, 2014, Trapezoidal/triangular intuitionistic fuzzy numbers versus interval-valued trapezoidal/triangular fuzzy numbers and applications to multicriteria decision making methods, Sofia, In Conf on IFSs, 10

Wei, 2010, Some arithmetic aggregation operators with intuitionistic trapezoidal fuzzy numbers and their application to group decision making, J Comput, 5, 345, 10.4304/jcp.5.3.345-351

Wan, 2010, Method of intuitionistic trapezoidal fuzzy number for multiattribute group decision, Control Decis, 25, 773

Wu, 2013, Same families of geometric aggregation operators with intuitionistic trapezoidal fuzzy numbers, Appl Math Model, 37, 318, 10.1016/j.apm.2012.03.001