Interval-valued (p,q,r)-spherical fuzzy sets and their applications in MCGDM and MCDM based on TOPSIS method and aggregation operators

被引:2
|
作者
Karaaslan, Faruk [1 ]
Karamaz, Fatih [1 ]
机构
[1] Cankiri Karatekin Univ, Fac Sci, Dept Math, TR-18100 Cankiri, Turkiye
关键词
(pqr)-spherical fuzzy sets; Interval-valued (pqr)-spherical fuzzy sets; Aggregation operator; Score function; Distance measure; Decision-making; FUNDAMENTAL PROPERTIES;
D O I
10.1016/j.eswa.2024.124575
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The (p,q,r)-Spherical fuzzy set is a useful generalization of other fuzzy structures such as fuzzy, intuitionistic fuzzy, Pythagorean fuzzy, picture fuzzy, q-rung orthopair fuzzy, spherical fuzzy, and T-spherical fuzzy sets. In this paper, we define concept of interval-valued (p,q,r)-spherical fuzzy set (IVpqr-SFS) and Set-theoretical and arithmetic operations of them. Two aggregation operators named interval-valued (p,q,r)-spherical fuzzy weighted arithmetic (IVpqr-SFWAA) and interval-valued (p,q,r)-spherical fuzzy weighted geometric (IVpqrSFWGA) aggregation operators are introduced for IVpqr-SF numbers (IVpqr-SFN) and their properties were examined. The proposed operators are explained with examples. Furthermore, the score and accuracy functions of an IVpqr-SFN are introduced. We also define distance measures between two same types IVpqr-SFSs based on Hamming, Euclidean, and Hausdorff distance measures. Moreover, a multi-criteria group decision-making (MCGDM) method is developed based on the TOPSIS method by using the proposed distance measures and score function, and a numerical example is given to show the process of the proposed MCGDM method. In addition, a multi-criteria decision-making (MCDM) method is developed using the proposed IVpqr-SFWAA, IVpqr-SFWGA operators, and an illustrative example is given to show the process of the proposed MCDM method. Finally, a comparative analysis is presented between the proposed methods and the existing methods.
引用
收藏
页数:28
相关论文
共 50 条
  • [21] A Novel Measured Function for MCDM Problem Based on Interval-Valued Intuitionistic Fuzzy Sets
    Hung, Kuo-Chen
    Tsai, Yuan-Cheng
    Lin, Kuo-Ping
    Julian, Peterson
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2010, E93D (11) : 3059 - 3065
  • [22] The interval-valued fuzzy TOPSIS method and experimental analysis
    Chen, Ting-Yu
    Tsao, Chueh-Yung
    FUZZY SETS AND SYSTEMS, 2008, 159 (11) : 1410 - 1428
  • [23] Extension of VIKOR method based on interval-valued fuzzy sets
    Behnam Vahdani
    Hasan Hadipour
    Jamshid Salehi Sadaghiani
    Maghsoud Amiri
    The International Journal of Advanced Manufacturing Technology, 2010, 47 : 1231 - 1239
  • [24] Extension of the ELECTRE method based on interval-valued fuzzy sets
    Behnam Vahdani
    Hasan Hadipour
    Soft Computing, 2011, 15 : 569 - 579
  • [25] Extension of the ELECTRE method based on interval-valued fuzzy sets
    Vahdani, Behnam
    Hadipour, Hasan
    SOFT COMPUTING, 2011, 15 (03) : 569 - 579
  • [26] Extension of VIKOR method based on interval-valued fuzzy sets
    Vahdani, Behnam
    Hadipour, Hasan
    Sadaghiani, Jamshid Salehi
    Amiri, Maghsoud
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2010, 47 (9-12): : 1231 - 1239
  • [27] Ranking method of interval-valued intuitionistic fuzzy numbers based on TOPSIS
    School of Science, Nanchang University, Nanchang
    330031, China
    Kongzhi yu Juece Control Decis, 11 (2014-2018):
  • [28] THE INTERVAL-VALUED FUZZY SETS BASED ON FLOU SETS
    Li, Hong-Xia
    Liu, Kun
    Gong, Zeng-Tai
    PROCEEDINGS OF 2013 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), VOLS 1-4, 2013, : 223 - 228
  • [29] MADM method based on cross-entropy and extended TOPSIS with interval-valued intuitionistic fuzzy sets
    Zhang, Huimin
    Yu, Liying
    KNOWLEDGE-BASED SYSTEMS, 2012, 30 : 115 - 120
  • [30] Algebraic structure through interval-valued fuzzy signature based on interval-valued fuzzy sets
    Sangeetha Palanisamy
    Jayaraman Periyasamy
    Granular Computing, 2023, 8 (5) : 1081 - 1096