A new multi-criteria group decision-making approach based on q-rung orthopair fuzzy interaction Hamy mean operators

Xing, Yuping; Zhang, Runtong; Wang, Jun; Bai, Kaiyuan; Xue, Jing

doi:10.1007/s00521-019-04269-8

Cited by 63 publications

(38 citation statements)

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“…The concept of hesitant q-ROF aggregation operators was proposed by Hussain et al [13]. Xing et al [26] studied the point weighted aggregation operators and Xing et al [27] presented hamy mean operators in q-RO F environment.…”

Section: Introductionmentioning

confidence: 99%

Group-based generalized q-rung orthopair average aggregation operators and their applications in multi-criteria decision making

Hussain

Ali

Mahmood

et al. 2020

Complex Intell. Syst.

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The objective of this manuscript is to investigate the concept of generalized q-rung orthopair fuzzy sets (Gq-ROFSs) and group generalized q-rung orthopair fuzzy sets (GGq-ROFSs) by incorporating the concept of generalized parameter and group generalized parameters in q-rung orthopair fuzzy environment. The main advantage of generalized parameter in q-rung orthopair fuzzy environment is to reduce uncertain errors in the original information to ensure the expert's level of trust and improve the accuracy of final decision. On the base of generalized parameter, some aggregation operators are introduced such as generalized q-rung orthopair fuzzy average aggregation operators and group generalized q-rung orthopair fuzzy average aggregation operators and studied their related properties. Furthermore, a multi-criteria decision-making method technique based on proposed approach is presented. Finally, a numerical example is provided to illustrate the feasibility of the proposed methods and deliver the sensitivity analysis and comparative analysis, which show the superiority of developed approached than existing methods. Keywords q-rung orthopair fuzzy sets • Gq-ROFSs • GGq-ROFSs • Gq-ROF aggregation operators • GGq-ROF aggregation operators • MCDM

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Section: Introductionmentioning

confidence: 99%

Group-based generalized q-rung orthopair average aggregation operators and their applications in multi-criteria decision making

Hussain

Ali

Mahmood

et al. 2020

Complex Intell. Syst.

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show abstract

“…Hybrid operator-based approaches: For investigating the relationships between objects, the hybrid aggregation operators play an essential role in the realistic decision environment. Scholars have investigated various hybrid aggregation operators based on the q-ROFS, for example, Archimedean Bonferroni mean operators [14], Maclaurin symmetric mean operators [15], Muirhead mean operators [16], power Maclaurin symmetric mean operators [17], Heronian mean operators [18], partitioned Bonferroni mean operators [19], partitioned Maclaurin symmetric mean operators [20], and others [21][22][23][24][25][26][27][28][29][30][31][32][33]. Figure 1 presents the geometric representations of the IFSs, PFSs, and q-ROFSs.…”

Section: Introductionmentioning

confidence: 99%

Generalized complex q-rung orthopair fuzzy Einstein averaging aggregation operators and their application in multi-attribute decision making

Лю

Ali

Mahmood

2020

Complex Intell. Syst.

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The recently proposed q-rung orthopair fuzzy set, which is characterized by a membership degree and a non-membership degree, is effective for handling uncertainty and vagueness. This paper proposes the concept of complex q-rung orthopair fuzzy sets (Cq-ROFS) and their operational laws. A multi-attribute decision making (MADM) method with complex q-rung orthopair fuzzy information is investigated. To aggregate complex q-rung orthopair fuzzy numbers, we extend the Einstein operations to Cq-ROFSs and propose a family of complex q-rung orthopair fuzzy Einstein averaging operators, such as the complex q-rung orthopair fuzzy Einstein weighted averaging operator, the complex q-rung orthopair fuzzy Einstein ordered weighted averaging operator, the generalized complex q-rung orthopair fuzzy Einstein weighted averaging operator, and the generalized complex q-rung orthopair fuzzy Einstein ordered weighted averaging operator. Desirable properties and special cases of the introduced operators are discussed. Further, we develop a novel MADM approach based on the proposed operators in a complex q-rung orthopair fuzzy context. Numerical examples are provided to demonstrate the effectiveness and superiority of the proposed method through a detailed comparison with existing methods.

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“…Q-rung orthopair fuzzy set has gotten extensive research and application [2]- [6]. Some aggregation operators have been developed [7]- [27]. Liu and Wang developed the qrung orthopair fuzzy weighted averaging operator in [7] and developed some weighted generalized Maclaurin symmetric mean operators in [9].…”

Section: Introductionmentioning

confidence: 99%

New q-Rung Orthopair Hesitant Fuzzy Decision Making Based on Linear Programming and TOPSIS

Yang

Pang

2020

IEEE Access

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A new multi-criteria group decision-making approach based on q-rung orthopair fuzzy interaction Hamy mean operators

Cited by 63 publications

References 50 publications

Group-based generalized q-rung orthopair average aggregation operators and their applications in multi-criteria decision making

Group-based generalized q-rung orthopair average aggregation operators and their applications in multi-criteria decision making

Generalized complex q-rung orthopair fuzzy Einstein averaging aggregation operators and their application in multi-attribute decision making

New q-Rung Orthopair Hesitant Fuzzy Decision Making Based on Linear Programming and TOPSIS

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