Abstract
In multicriteria decision making (MCDM), multi-hesitant fuzzy linguistic term sets (MHFLTSs) can eliminate the limitations of hesitant fuzzy linguistic term sets (HFLTSs) and hesitant fuzzy linguistic sets (HFLSs), and emphasize the importance of a repeated linguistic term (LT). Meanwhile, there is usually an interrelation between criteria. The Maclaurin symmetric mean (MSM) operator can capture the interrelationships among multi-input arguments. The purpose of this paper is to integrate MHFLTSs with MSM operators and to solve MCDM problems. Firstly, we develop the generalized MSM operator for MHFLTSs (MHFLGMSM), the generalized geometric MSM operator for MHFLTSs (MHFLGGMSM), the weighted generalized MSM operator for MHFLTSs (WMHFLGMSM) and the weighted generalized geometric MSM operator for MHFLTSs (WMHFLGGMSM), respectively. Then, we discuss their properties and some special cases. Further, we present a novel method to deal with MCDM problems with the MHFLTSs based on the proposed MSM operators. Finally, an illustrative example about how to select the best third-party logistics service provider is supplied to demonstrate the practicality and reliability of the proposed approaches in comparison with some existing approaches.
Highlights
Because human preferences are inherently vague, it is more suitable to deal with uncertainty and imprecise information by linguistic terms (LTs)
A multi-hesitant fuzzy linguistic term sets (MHFLTSs) is an extension of hesitant fuzzy linguistic sets (HFLSs) and hesitant fuzzy linguistic term sets (HFLTSs), which can preserve the frequencies of repeated
The Maclaurin symmetric mean (MSM) operator can take into account the correlativity among multi-inputs
Summary
Because human preferences are inherently vague, it is more suitable to deal with uncertainty and imprecise information by linguistic terms (LTs). Since Zadeh [1] presented the fuzzy linguistic technique in 1975, which utilized linguistic variables (LVs) to describe qualitative information, some methods based on LVs have been utilized in a number of areas, such as supply chain management [2], qualify function deploy [3], health care system [4], housing marker [5], risk evaluation [6], etc. If the qualitative information is only represented by a single LT, it might sometimes not accurately reflect what it means. When the decision-making problems become more ambiguous, the experts might be hesitant among several LTs and need two or more LTs to express their preference.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
