Abstract
Single-valued trapezoidal neutrosophic number (SVTrNN), an extension of single-valued neutrosophic set, effectively deals with indeterminate and incomplete information in multi-attribute decision making (MADM) problem. In this paper, we extend the grey relational analysis (GRA) method for solving SVTrNN based MADM problem, where the weight information of attributes is partially known or completely unknown. Following the classical GRA method, we define grey relational co-efficient using a new distance measure. We develop two optimization models to determine the weights of the attributes. We calculate grey positive and negative relational degrees and define the relative closeness co-efficient of each alternative to determine the best alternative. We take a numerical example to validate the proposed approach and compare the proposed method with other exiting methods. It is observed from the numerical study that the proposed GRA method has an advantage over the existing methods for solving SVTrNN based MADM problem with partially known or completely unknown attribute weight information.
Sign-in/Register to access full text options 
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.
