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Z-TOPSIS approach for performance assessment using fuzzy similarity

Research output: Chapter in Book/Report/Conference proceedingConference contribution

This paper presents fuzzy similarity based Fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) for z-numbers. The classical fuzzy TOPSIS techniques use closeness coefficient to determine the rank order by calculating Fuzzy Positive Ideal Solution (FPIS) and Fuzzy Negative Ideal Solution (FNIS) simultaneously. The authors propose fuzzy similarity to replace closeness coefficient by doing ranking evaluation. Fuzzy similarity is used to calculate the similarity between two fuzzy ratings (FPIS and FNIS). Fuzziness is not sufficient enough when dealing with real information and a degree of reliability of the information is very critical. Hence, the implementation of z-numbers is taken into consideration as they can capture better the knowledge of human being and are extensively used in uncertain information development to deal with linguistic decision making problems. A numerical example is given to illustrate the application of the proposed technique in ranking company performance assessment. The results show that it is highly feasible to use the proposed technique in performance assessment.
Original languageEnglish
Title of host publicationProceedings of the 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Number of pages6
ISBN (Electronic)978-1509060344
ISBN (Print) 978-1509060351
Publication statusPublished - 24 Aug 2017
Event2017 IEEE International Conference on Fuzzy Systems - Royal-Continental Hotel, Naples, Italy
Duration: 9 Jul 201712 Jul 2017

Publication series

NameIEEE FUZZ-IEEE Proceedings Series
ISSN (Electronic)1558-4739


Conference2017 IEEE International Conference on Fuzzy Systems
Internet address



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    Accepted author manuscript (Post-print), 241 KB, PDF document

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