A Method to Multi-Attribute Group Decision-Making Problem with Complex q-Rung Orthopair Linguistic Information Based on Heronian Mean Operators

• Published in: International journal of computational intelligence systems Vol. 12; no. 2; pp. 1465 - 1496
• Main Authors: Liu, Peide, Ali, Zeeshan, Mahmood, Tahir
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.01.2019; Springer Nature B.V; Springer
• Subjects: Complex q-rung orthopair fuzzy sets; Complex q-rung orthopair linguistic sets; Decision making; Fuzzy sets; Geometric Heronian mean operators; Heronian mean operators; Linguistic sets; Linguistics; Operators (mathematics); Research Article; Geometric Heronian mean operators; Complex q-rung orthopair fuzzy sets; Complex q-rung orthopair linguistic sets; Heronian mean operators; Linguistic sets
• ISSN: 1875-6891; 1875-6883; 1875-6883
• DOI: 10.2991/ijcis.d.191030.002

The notions of complex q-rung orthopair fuzzy sets (Cq-ROFSs) and linguistic sets (LSs) are two different concepts to deal with uncertain information in multi-attribute group decision-making (MAGDM) problems. The Heronain mean (HM) and geometric Heronain mean (GHM) operators are an effective tool used to aggregate some q-rung orthopair linguistic fuzzy numbers (q-ROLFNs) into a single element. The purpose of this manuscript is to propose a new concept called complex q-rung orthopair linguistic sets (Cq-ROLSs) to cope with complex uncertain information in real decision-making problems. Then the fundamental laws and their examples of the Cq-ROLSs are also given. Furthermore, the notions of complex q-rung orthopair linguistic Heronian mean (Cq-ROLHM) operator, complex q-rung orthopair linguistic weighted Heronian mean (Cq-ROLWHM) operator, complex q-rung orthopair linguistic geometric Heronian mean (Cq-ROLGHM) operator, complex q-rung orthopair linguistic weighted geometric Heronian mean (Cq-ROLWGHM) operator are proposed and their basic properties are also discussed. Moreover, we develop a novel approach to MAGDM using proposed operators and a numerical example is used to describe the flexibility and explicitly of the initiated operators. In last, the comparison between proposed method and existing work is also discussed in detail.