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A Hybrid Multiple-Attribute Decision-Making Model Under Complex Q-Rung Orthopair Fuzzy Hamy Mean Aggregation Operators
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Author(s): Sumera Naz (Department of Mathematics, Division of Science and Technology, University of Education, Lahore, Pakistan), Muhammad Akram (Department of Mathematics, University of the Punjab, New Campus, Lahore, Pakistan)and Aatifa Saeed (School of Mathematics, Minhaj University, Lahore, Pakistan)
Copyright: 2022
Pages: 43
Source title:
Handbook of Research on Advances and Applications of Fuzzy Sets and Logic
Source Author(s)/Editor(s): Said Broumi (Laboratory of Information Processing, Faculty of Science Ben M’Sik, University Hassan II, Casablanca, Morocco & Regional Center for the Professions of Education and Training (CRMEF), Casablanca-Settat, Morocco)
DOI: 10.4018/978-1-7998-7979-4.ch007
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Abstract
The concept of complex q-rung orthopair fuzzy sets (Cq-ROFSs) serves as an extension of the current complex orthopair fuzzy sets, including complex intuitionistic fuzzy sets and complex Pythagorean fuzzy sets. Hamy mean (HM) aggregation operator is a useful tool to model the interrelationship between attributes. In this contribution, the traditional HM is generalized to aggregate complex q-rung orthopair fuzzy information, and a multi-attribute decision-making (MADM) approach is proposed to solve decision-making problems with complex q-rung orthopair fuzzy information. Firstly, the complex q-rung orthopair fuzzy Hamy mean (Cq-ROFHM) operator and the complex q-rung orthopair fuzzy dual Hamy mean (Cq-ROFDHM) operator along with its weighted forms are proposed. Moreover, to deal with MADM problems, a novel approach is developed based on the proposed HM operators under complex q-rung orthopair fuzzy framework. Lastly, a numerical model is described for the selection of enterprise resource planning (ERP) systems to demonstrate the use of the generated technique and exhibit its adequacy.
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