Z-TOPSIS approach for performance assessment using fuzzy similarity

Ku Muhammad Naim Ku Khalif; Alexander Gegov; Ahmad Syafadhli Abu Bakar

doi:10.1109/FUZZ-IEEE.2017.8015458

Z-TOPSIS approach for performance assessment using fuzzy similarity

Ku Muhammad Naim Ku Khalif, Alexander Gegov, Ahmad Syafadhli Abu Bakar

School of Computing

University of Malaya

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

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 language	English
Title of host publication	Proceedings of the 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	6
ISBN (Electronic)	978-1509060344
ISBN (Print)	978-1509060351
DOIs	https://doi.org/10.1109/FUZZ-IEEE.2017.8015458
Publication status	Published - 24 Aug 2017
Event	2017 IEEE International Conference on Fuzzy Systems - Royal-Continental Hotel, Naples, Italy Duration: 9 Jul 2017 → 12 Jul 2017 https://www.fuzzieee2017.org/index.html

Publication series

Name	IEEE FUZZ-IEEE Proceedings Series
Publisher	IEEE
ISSN (Electronic)	1558-4739

Conference

Conference	2017 IEEE International Conference on Fuzzy Systems
Country/Territory	Italy
City	Naples
Period	9/07/17 → 12/07/17
Internet address	https://www.fuzzieee2017.org/index.html

Keywords

multi criteria decision making
fuzzy TOPSIS
fuzzy similarity
z-numbers
human intuition

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10.1109/FUZZ-IEEE.2017.8015458

FUZZIEEE_PAPER_2
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Accepted author manuscript (Post-print), 241 KB

Cite this

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title = "Z-TOPSIS approach for performance assessment using fuzzy similarity",

abstract = "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.",

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Ku Khalif, KMN, Gegov, A & Abu Bakar, AS 2017, Z-TOPSIS approach for performance assessment using fuzzy similarity. in Proceedings of the 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE FUZZ-IEEE Proceedings Series, Institute of Electrical and Electronics Engineers Inc., 2017 IEEE International Conference on Fuzzy Systems, Naples, Italy, 9/07/17. https://doi.org/10.1109/FUZZ-IEEE.2017.8015458

Z-TOPSIS approach for performance assessment using fuzzy similarity. / Ku Khalif, Ku Muhammad Naim; Gegov, Alexander; Abu Bakar, Ahmad Syafadhli.
Proceedings of the 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). Institute of Electrical and Electronics Engineers Inc., 2017. (IEEE FUZZ-IEEE Proceedings Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Z-TOPSIS approach for performance assessment using fuzzy similarity

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Keywords

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