Journal
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
Volume 13, Issue 3, Pages 609-632Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s13042-020-01269-2
Keywords
Interval-valued q-rung orthopair fuzzy sets; Aggregation operators; Group decision making; Product appearance design evaluation
Categories
Funding
- National Natural Science Foundation of China [71801175, 71871171, 71971182, 72031009]
- Ministry of Education of Humanities and Social Science Foundation of China [20YJCZH210]
- Natural Science Foundation of Hunan Province, China [2020JJ5112]
- Theme-based Research Projects of the Research Grants Council [T32-101/15-R]
- Spanish Ministry of Economy and Competitiveness through the Spanish National Research Project [PGC2018-099402-B-I00]
- postdoctoral fellowship Ramon y Cajal [RyC-2017-21978]
- Ger/HKJRS project [G-CityU103/17]
- City University of Hong Kong SRG [7004969]
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The concept of Yager's q-rung orthopair fuzzy set has attracted considerable attention as a tool for representing imprecision and uncertainty. This study proposes several continuous IVQROF aggregation operators and a parameter optimization model for group decision-making, with a case study demonstrating the rationality and efficiency of the proposed operators.
The notion of Yager's q-rung orthopair fuzzy set (QROFS) have gained considerable and continuously increasing attention as a useful tool for imprecision and uncertainty representation due to its capability to discard the constraints on the membership and nonmembership functions as generally required by its intuitionistic fuzzy counterpart. Among the generalizations and variants established in the past few years, the interval-valued QROFSs (IVQROFSs) have been diffusely considered to be a powerful generalization of the interval-valued fuzzy sets. The continuous ordered weighted averaging (COWA) operator has been extended successfully to some special cases of IVQROFSs, including interval-valued intuitionistic and Pythagorean fuzzy sets. Thus, to expand on previous studies, several continuous IVQROF (C-IVQROF) aggregation operators are proposed in this study. First, the dual C-GOWA operator is defined on the basis of the continuous generalized ordered weighted averaging (C-GOWA) operator and Yager class of fuzzy negation. Subsequently, the C-IVQROFOWA operator with two independent parameters is constructed, and the weighted C-IVQROFOWA operator is then proposed for aggregating a collection of IVQROFSs. The C-IVQROFOWA operator and its weighted version can model commendably the attitudinal characteristics of the decision-maker. Second, a parameter optimization model and its algorithm-solving strategy driven by consensus measures are built to develop a group decision-making method. Finally, a case study to evaluate the SmartWatch design alternatives is provided to demonstrate the proposed approach, and the results of a comparative analysis verify the rationality and efficiency of the proposed operators.
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