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International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 3/2022

24-01-2021 | Original Article

q-ROF-SIR methods and their applications to multiple attribute decision making

Authors: Hua Zhu, Jianbin Zhao, Hua Li

Published in: International Journal of Machine Learning and Cybernetics | Issue 3/2022

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Abstract

q-rung orthopair fuzzy set (q-ROFS) is a useful tool to express uncertain information. With the parameter q increasing, q-ROFSs have broader space for describing uncertain information than intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs). This paper extends the superiority and inferiority ranking (SIR) methods to solve multiple attribute decision making (MADM) problems within the q-ROF environment, named q-ROF-SIR methods. In the q-ROF-SIR methods, the possibility degree (PD) for q-rung orthopair fuzzy numbers (q-ROFNs) is introduced to improve the preference intensity. Further, the q-ROF entropy weight (q-ROF-EW) method is constructed to determine the attribute weights suppose the weights of attribute are unknown. Finally, the effectiveness and applicability of the q-ROF-SIR methods are verified.
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Metadata
Title
q-ROF-SIR methods and their applications to multiple attribute decision making
Authors
Hua Zhu
Jianbin Zhao
Hua Li
Publication date
24-01-2021
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 3/2022
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-020-01267-4

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