PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Powiadomienia systemowe
  • Sesja wygasła!
  • Sesja wygasła!
Tytuł artykułu

A novel multiple attribute decision-making method based on Schweizer-Sklar t-norm and t-conorm with q-rung dual hesitant fuzzy information

Autorzy
Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The recently proposed q-rung dual hesitant fuzzy sets (q-RDHFSs) not only deal with decision makers’ (DMs’) hesitancy and uncertainty when evaluating the performance of alternatives, but also give them great liberty to express their assessment information comprehensively. This paper aims to propose a new multiple attribute decision-making (MADM) method where DMs’ evaluative values are in form of q-rung dual hesitant fuzzy elements (q-RDHFEs). Firstly, we extend the powerful Schweizer-Sklar q-norm and t-conorm (SSTT) to q-RDHFSs and propose novel operational rules of q-RDHFEs. The prominent advantage of the proposed operations is that they have important parameters q and r, making the information fusion procedure more flexible. Secondly, to effectively cope with the interrelationship among attributes, we extend the Hamy mean (HM) to q-RDHFSs and based on the newly developed operations, we propose the q-rung dual hesitant fuzzy Schweizer-Sklar Hamy mean (q-RDHFSSHM) operator, and the q-rung dual hesitant fuzzy Schweizer-Sklar weighted Hamy mean (q-RDHFSSWHM) operator. The properties of the proposed operators, such as idempotency, boundedness and monotonicity are discussed in detail. Third, we propose a new MADM method based on the q-RDHFSSWHM operator and give the main steps of the algorithm. Finally, the effectiveness, flexibility and advantages of the proposed method are discussed through numerical examples.
Rocznik
Strony
175--228
Opis fizyczny
Bibliogr. 59 poz., rys., tab., wzory
Twórcy
autor
  • School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
autor
  • School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China
Bibliografia
  • [1] J. Wang, X. Shang, X. Feng and M. Sun: A novel multiple attribute decision making method based on q-rung dual hesitant uncertain linguistic sets and Muirhcad mean. Archives of Control Sciences, 30(2), (2020), 233-272. DOI: 10.24425/aes.2020.133499.
  • [2] X. Tang and G. Wee Dual hesitant Pythagorean fuzzy Bonferroni mean operators in multi-attribute decision making. Archives of Control Sciences, 29(2), (2019), 339-386. DOI: 10.24425/acs.2019.129386.
  • [3] P. Liu, H. Xu and Y. Geng: Normal wiggly hesitant fuzzy linguistic power Hamy mean aggregation operators and their application to multi-attribute decision making. Computers & Industrial Engineering, 140 (2020), 106224. DOI: 10.1016/j.cic.2019.106224.
  • [4] B.P. Josui and A. Gegov: Confidence levels q-rung orthopair fuzzy aggregation operators and its applications to MCDM problems. International Journal of Intelligent Systems, 35(1), (2020), 125-149. DOI: 10.1002/int.22203.
  • [5] V. Mohagheghi and S.M. Mousavi: A new framework for high-technology project evaluation and project portfolio selection based on Pythagorean fuzzy WASPAS, MOORA and mathematical modeling. Iranian Journal of Fuzzy Systems, 16(6), (2019), 89-106. DOI: 10.22111/IJFS.2019.5022.
  • [6] Biswas and A. Sarkar: Development of dual hesitant fuzzy prioritized operators based on Einstein operations with their application to multi-criteria group decision making. Archives of Control Sciences, 28(4), (2018), 527-549. DOI: 10.24425/acs.2018.125482.
  • [7] L. Li, R. Zhang and X. Shang: Some q-rung orthopair linguistic Heronian mean operators with their application to multi-attribute group decision making. Archives of Control Sciences, 28(4), (2018), 551-583. DOI: 10.24425/acs.2018.125483.
  • [8] K.T. Atanassov: Intuitionistic fuzzy sets. Fuzzy Sets and System, 20 (1986), 87-96.
  • [9] R.R. Yager: Pythagorean membership grades in multicritcria decision-making. IEEE Transactions and Fuzzy Systems, 22(4), (2013), 958-965. DOI: 10.1109/TFUZZ.2013.2278989.
  • [10] Z. Zhang and W. Pedrycz: A consistency and consensus-based goal programming method for group decision-making with interval-valued intuitionistic multiplicative preference relations. IEEE Transactions on Cybernetics, 49(10), (2018), 3640-3654. DOI: 10.1109/TCYB.2018.2842073.
  • [11] H. Garg and K. Kumar: Multi-attribute decision-making based on power operators for linguistic intuitionistic fuzzy set using set pair analysis. Expert Systems, 36(4), (2019), e12428. DOI: 10.1111/exsy.12428.
  • [12] S. Zeng, S. Chen and L. Kuo: Multi-attribute decision-making based on novel score function of intuitionistic fuzzy values and modified VIKOR method. Information Sciences, 488 (2019), 76-92. DOI: 10.1016/j.ins.2019.03.018
  • [13] H. Garg and D. Rani: New generalised Bonferroni mean aggregation operators of complex intuitionistic fuzzy information based on Archimedean t-norm and t-conorm. Journal of Experimental Theoretical Artificial Intelligence, 32(1), (2019), 81-109. DOI: 10.1080/0952813X.2019.1620871.
  • [14] S. Liu, W. Yu, L. Liu and Y. Hu: Variable weights theory and its application to multi-attribute group decision-making with intuitionistic fuzzy numbers on determining decision maker's weights. PLoS One, 14(3), (2019), e0212636. DOI: 10.1371/journal.pone.0212636.
  • [15] P. Liu and D. Li: Some Muirhead mean operators for intuitionistic fuzzy numbers and their applications to group decision-making. PLoSOne, 12(1), (2017), e0168767. DOI: 10.1371/journal.pone.0168767.
  • [16] Z. Hussian and M.S. Yang: Distance and similarity measures of Pythagorean fuzzy sets based on the Hausdorff metric with application to fuzzy TOPSIS. International Journal of Intelligent Systems, 34 (2019), 2633-2654. DOI: 10.1002/int.22169.
  • [17] R. Zhang, J. Wang, X. Zhu, M. Xia and M. Yu: Some generalized Pythagorean fuzzy Bonferroni mean aggregation operators with their application to multi-attribute group decision-making. Complexity, (2017), Article ID: 5937376. DOI: 10.1155/2017/5937376.
  • [18] L. Li, R. Zhang, J. Wang, X. Zhu and Y. Xing: Pythagorean fuzzy power Muirhead mean operators with their application to multi-attribute decision-making. Journal of Intelligent and Fuzzy Systems, 35(2), (2018), 2035-2050. DOI: 10.3233/JIFS-171907.
  • [19] Y. Xing, R. Zhang, J. Wang and X. Zhu: Some new Pythagorean fuzzy Choque t-Frank aggregation operators for multi-attribute decision-making. International Journal of Intelligent Systems, 33(11), (2018), 2189-2215. DOI: 10.1002/int.22025.
  • [20] R. Liang, S. He, J. Wang, K. Chen and L. Li: An extended MABAC method for multi-criteria group decision-making problems based on correlative inputs of intuitionistic fuzzy information. Computational and Applied Mathematics, 38(3), (2019), 112. DOI: 10.1007/s40314-019-0886-5.
  • [21] T. Rashid, S. Faizi and S. Zafar: Outranking method for intuitionistic 2-tuple fuzzy linguistic information model in group decision-making. Soft Computing, 23(15), (2018), 6145-6155. DOI: 10.1007/s00500-018-3268-9.
  • [22] K. Guo and J. Zang: Knowledge measure for interval-valued intuitionistic fuzzy sets and its application to decision-making under uncertainty. Soft Computing, 23(16), (2018), 6967-6978. DOI: 10.1007/s00500-018-3334-3.
  • [23] X. Zhu, K. Bai, J. Wang, R. Zhang and Y. Xing: Pythagorean fuzzy interaction power partitioned Bonferroni means with applications to multi-attribute group decision-making. Journal of Intelligent & Fuzzy Systems, 36(4), (2019), 3423-3438. DOI: 10.3233/JIFS-181171.
  • [24] Y. Xu, X. Shang and J. Wang: Pythagorean fuzzy interaction Muirhead means with their application to multi-attribute group decision-making. Information, 9(1), (2018), 157. DOI: 10.3390/info9070157.
  • [25] J. Lu, X. Tang, G. Wet, C. Wei and Y. Wei: Bidirectional project method for dual hesitant Pythagorean fuzzy multiple attribute decision-making and their application to performance assessment of new rural construction. International Journal of Intelligent Systems, 34(8), (2019), 1920-1934. DOI: 10.1002/int.22126.
  • [26] N. Jan, M. Aslam, K. Ullah, T. Mahmood and J. Wang: An approach towards decision-making and shortest path problems using the concepts of interval-valued Pythagorean fuzzy information. International Journal of Intelligent Systems, 34(10), (2019), 2403-2428. DOI: 10.1002/int.22154.
  • [27] S. Xian, Y. Xiao, L. Li and D. Yu: Trapezoidal Pythagorean fuzzy linguistic entropic combined ordered weighted Minkowski distance operator based on preference relations. International Journal of Intelligent Systems, 34(9), (2019), 2196-2224. DOI: 10.1002/int.22139.
  • [28] P. Liu, S.M. Chen and Y. Wang: Multi-attribute group decision making based on intuitionistic fuzzy partitioned Maclaurin symmetric mean operators. Information Sciences, 512 (2020), 830-854. DOI: 10.1016/j.ins.2019.10.013.
  • [29] R.R. Yager: Generalized orthopair fuzzy sets. IEEE Transactions on Fuzzy Systems, 25(5), (2016), 1222-1230. DOI: 10.1109/TFUZZ.2016.2604005.
  • [30] P. Liu and P. Wang: Some q-rung orthopair fuzzy aggregation operators and their applications to multiple-attribute decision-making. International Journal of Intelligent Systems, 33(2), (2018), 259-280. DOI: 10.1002/int.21927.
  • [31] P. Liu and J. Liu: Some q-rung orthopair fuzzy Bonferroni mean operators and their application to multi-attribute group decision-making. International Journal of Intelligent Systems, 33(2), (2018), 315-347. DOI: 10.1002/int.21933.
  • [32] P. Liu and P. Wang: Multiple-attribute decision-making based on Archimedean Bonferroni operators of q-rung orthopair fuzzy numbers. IEEE Transactions on Fuzzy Systems, 27(5), (2018), 834-848. DOI: 10.1109/TFUZZ.2018.2826452.
  • [33] G. Wei, H. Gao and Y. Wei: Some q-rung orthopair fuzzy Heronian mean operators in multiple attribute decision-making. International Journal of Intelligent Systems, 33(7), (2018), 1426-1458. DOI: 10.1002/int.21985.
  • [34] J. Wang, G.W. Wei, J.P. Lu, RE. Alsaadi, T. Hayat, C. Wei and Y. Zhang: Some q-rung orthopair fuzzy Hamy mean operators in multiple attribute decision-making and their application to enterprise resource planning systems selection. International Journal of Intelligent Systems, 34(10), (2019), 2429-2458. DOI: 10.1002/int.22155.
  • [35] G. Wei, C. Wei, J. Wang, H. Gao and Y. Wei: Some q-rung orthopair fuzzy Maclaurin symmetric mean operators and their applications to potential evaluation of emerging technology commercialization. International Journal of Intelligent Systems, 34(1), (2019), 50-81. DOI: 10.1002/int.22042.
  • [36] P. Liu, S. Chen and P. Wang: Multiple-attribute group decision-making based on q-rung orthopair fuzzy power Maclaurin symmetric mean operators. IEEE Transactions on Systems Man Cybernetics-Systems, 50(10), (2018), 1-16. DOI: 10.1109/TSMC.2018.2852948.
  • [37] J. Wang, R. Zhang, X. Zhu, Z. Zhou, X. Shang and W. Li: Some q-rung orthopair fuzzy Muirhead means with their application to multi-attribute group decision-making. Journal of Intelligent & Fuzzy Systems, 36(2), (2019), 1599-1614. DOI: 10.3233/JIFS-18607.
  • [38] W. Yang and Y. Pang: New q-rung orthopair fuzzy partitioned Bonferroni mean operators and their application in multiple attribute decision-making. International Journal of Intelligent Systems, 34(3), (2019), 439-476. DOI: 10.1002/int.22060.
  • [39] Z. Liu, S. Wang and P. Liu: Multiple attribute group decision-making based on q-rung orthopair fuzzy Heronian mean operators. International Journal of Intelligent Systems, 33(12), (2018), 2341-2363. DOI: 10.1002/int.22032.
  • [40] K. Bai, X. Zhu, J. Wang and R. Zhang: Some partitioned Maclaurin symmetric mean based on q-rung orthopair fuzzy information for dealing with multi-attribute group decision-making. Symmetry, 10(9), (2018), 383. DOI: 10.3390/sym10090383.
  • [41] J. Wang, H. Gao, G.W. Wei and Y. Wei: Methods for multiple-attribute group decision making with q-rung interval-valued orthopair fuzzy information and their applications to the selection of green suppliers. Symmetry-Basel, 11(1), (2019), 56. DOI: 10.3390/sym11010056.
  • [42] P. Liu and W. Liu: Multiple-attribute group decision-milking based on power Bonferroni operators of linguistic q-rung orthopair fuzzy number. International Journal of Intelligent Systems, 34(4), (2019), 652-689. DOI: 10.1002/int.22071.
  • [43] Y. Xing, R. Zhang, X. Zhu and K. Bai: 2-rung orthopair fuzzy uncertain linguistic Choquel integral operators and their application to multi-attribute decision making. Journal of Intelligent & Fuzzy Systems, 37(1), (2019), 1123-1139. DOI: 10.3233/JIFS-182581.
  • [44] Y. Xu, X. Shang, J. Wang, W. Wu and H. Huang: Some q-rung dual hesitant fuzzy Heronian mean operators with their application to multiple attribute group decision-making. Symmetry, 10(10), (2018), 472. DOI: 10.3390/sym10100472.
  • [45] P. Wang and P. Liu: Some Maclaurin symmetric mean aggregation operators based on Schweizer-Sklar operations for intuitionistic fuzzy numbers and their application to decision-making. Journal of Intelligent & Fuzzy Systems, 36(4), (2019), 3801-3824. DOI: 10.3233/JIFS-18801.
  • [46] P. Liu and P. Wang: Some interval-valued intuitionistic fuzzy Schweizer-Sklar power aggregation operators and their application to supplier selection. International Journal of Systems Science,49(6), (2018), 1188-1211. DOI: 10.1080/00207721.2018.1442510.
  • [47] P. Liu, Q. Kuan and T. Mahmood: Multiple-attribute decision-making based on single-valued neutrosophic Schweizer-Sklar prioritized aggregation operator. Cognitive Systems Research, 57 (2019), 175-196. DOI: 10.1016/j.cogsys.2018.10.005.
  • [48] H. Zhang, F. Wang and Y. Ceng: Multi-criteria decision-making method based on single-valued neutrosophic Schweizer-Sklar Muirhead mean aggregation operators. Symmetry, 11(2), (2019), 152. DOI: 10.3390/sym11020152.
  • [49] Z. Li, H. Gao and G. Wei: Methods for multiple attribute group decision-making based on intuitionistic fuzzy Dombi Hamy mean operators. Symmetry, 10(11), (2018), 574. DOI: 10.3390/sym10110574.
  • [50] L. Wu, J. Wang and H. Gao: Models for competiveness evaluation of tourist destination with some interval-valued intuitionistic fuzzy Hamy mean operators. Journal of Intelligent & Fuzzy Systems, 36(6), (2019), 5693-5709. DOI: 10.3233/JIFS-181545.
  • [51] Z. Li, G. Wei and M. Lu: Pythagorean fuzzy Hamy mean operators in multiple attribute group decision-making and their application to supplier selection. Symmetry, 10(10), (2018), 505. DOI: 10.3390/sym10100505.
  • [52] P. Lai, Q. Khan and T. Mahmood: Application of interval neutrosophic power Hamy mean operators in MAGDM. Informatica, 30(2), (2019), 293-325. DOI: 10.15388/Informalica.2019.207.
  • [53] G. Wei and M. Lu: Dual hesitant Pythagorean fuzzy Hamacher aggregation operators in multiple attribute decision-making. Archives of Control Sciences, 27(3), (2017), 365-395. DOI: 10.1515/acsc-2017-0024.
  • [54] B. Zhu, Z. Xu and M. Xia: Dual hesitant fuzzy sets. Journal of Applied Mathematics, 2012 (2012), Article ID: 879629. DOI: 10.1155/2012/879629.
  • [55] T. Hara, M. Uchiyama and S.F. Takahasi: A refinement of various mean inequalities. Journal of Inequalities and Applications, 2 (1998), 387-395.
  • [56] H. Wang, X. Zhao and G. Wei: Dual hesitant fuzzy aggregation operators in multiple attribute decision-making. Journal of Intelligent & Fuzzy Systems, 26(5), (2014), 2281-2290. DOI: 10.3233/IFS-130901.
  • [57] A. Donabedian: The quality of care, how can it be assessed. JAMA. 260( 12), (1988), 1743-1748. DOI: 10.1001/jama.1988.03410120089033.
  • [58] M. Tang, J. Wang, J. Lu, G. Wei, C. Wei and Y. Wei: Dual hesitant Pythagorean fuzzy Heronian mean operators in multiple attribute decision-making. Mathematics, 7(4), (2019), 344. DOI: 10.3390/math7040344.
  • [59] Z. Xu and R.R. Yager: Intuitionistic fuzzy Bonferroni means. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics), 41(2), (2010), 568-578. DOI: 10.1109/TSMCB.2010.2072918.
Uwagi
1. This work is supported by Fundamental Research Funds for the Central Universities (Grant Number: 2021YJS056).
2. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-92b748db-ac46-4968-93c3-9a0086165631
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.