Fuzzy systems with multiple rule bases for selection of alternatives using TOPSIS

Abdul  Yaakob; Alexander Gegov; Mohamed Bader-El-Den; Siti Fatimah  Abdul Rahman

doi:10.1109/FUZZ-IEEE.2016.7737948

Fuzzy systems with multiple rule bases for selection of alternatives using TOPSIS

Abdul Yaakob, Alexander Gegov, Mohamed Bader-El-Den, Siti Fatimah Abdul Rahman

School of Computing

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

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Abstract

This paper introduces a novel modification of the technique for ordering of preference by similarity to ideal solution (TOPSIS) method and uses a fuzzy system with multiple rule bases to solve multi-criteria decision making problems where both benefit and cost criteria are presented as subsystems. Thus, the decision maker evaluates the performance of each alternative for optimization and further observes the performance for both benefit and cost criteria. This approach improves significantly the transparency of the TOPSIS method while ensuring high effectiveness in comparison to established methods. To ensure practicality and effectiveness of the proposed method, a traded equity case study is considered. Furthermore, the ranking based on the proposed method is validated comparatively using spearman rho correlation. The proposed method
outperforms the existing TOPSIS methods in terms of ranking for the case study under consideration.

Original language	English
Title of host publication	Proceedings of the 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2083-2090
Number of pages	8
ISBN (Electronic)	978-1509006267
ISBN (Print)	978-1509006274
DOIs	https://doi.org/10.1109/FUZZ-IEEE.2016.7737948
Publication status	Published - 10 Nov 2016
Event	2016 IEEE World Congress on Computational Intelligence - Vancouver, Canada Duration: 25 Jul 2016 → 29 Jul 2016

Conference

Conference	2016 IEEE World Congress on Computational Intelligence
Abbreviated title	IEEE WCCI
Country/Territory	Canada
City	Vancouver
Period	25/07/16 → 29/07/16

Keywords

fuzzy systems
multiple rule bases
TOPSIS
multicriteria decision making
spearman rho correlation
traded equity

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10.1109/FUZZ-IEEE.2016.7737948

WCCI_PAPERAccepted author manuscript (Post-print), 1.61 MB

Cite this

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title = "Fuzzy systems with multiple rule bases for selection of alternatives using TOPSIS",

abstract = "This paper introduces a novel modification of the technique for ordering of preference by similarity to ideal solution (TOPSIS) method and uses a fuzzy system with multiple rule bases to solve multi-criteria decision making problems where both benefit and cost criteria are presented as subsystems. Thus, the decision maker evaluates the performance of each alternative for optimization and further observes the performance for both benefit and cost criteria. This approach improves significantly the transparency of the TOPSIS method while ensuring high effectiveness in comparison to established methods. To ensure practicality and effectiveness of the proposed method, a traded equity case study is considered. Furthermore, the ranking based on the proposed method is validated comparatively using spearman rho correlation. The proposed methodoutperforms the existing TOPSIS methods in terms of ranking for the case study under consideration.",

keywords = "fuzzy systems, multiple rule bases, TOPSIS, multicriteria decision making, spearman rho correlation, traded equity",

author = "Abdul Yaakob and Alexander Gegov and Mohamed Bader-El-Den and {Abdul Rahman}, {Siti Fatimah}",

year = "2016",

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booktitle = "Proceedings of the 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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note = "2016 IEEE World Congress on Computational Intelligence, IEEE WCCI ; Conference date: 25-07-2016 Through 29-07-2016",

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Yaakob, A, Gegov, A , Bader-El-Den, M & Abdul Rahman, SF 2016, Fuzzy systems with multiple rule bases for selection of alternatives using TOPSIS. in Proceedings of the 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). Institute of Electrical and Electronics Engineers Inc., pp. 2083-2090, 2016 IEEE World Congress on Computational Intelligence, Vancouver, Canada, 25/07/16. https://doi.org/10.1109/FUZZ-IEEE.2016.7737948

Fuzzy systems with multiple rule bases for selection of alternatives using TOPSIS. / Yaakob, Abdul ; Gegov, Alexander ; Bader-El-Den, Mohamed et al.
Proceedings of the 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). Institute of Electrical and Electronics Engineers Inc., 2016. p. 2083-2090.

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

TY - GEN

T1 - Fuzzy systems with multiple rule bases for selection of alternatives using TOPSIS

AU - Yaakob, Abdul

AU - Gegov, Alexander

AU - Bader-El-Den, Mohamed

AU - Abdul Rahman, Siti Fatimah

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N2 - This paper introduces a novel modification of the technique for ordering of preference by similarity to ideal solution (TOPSIS) method and uses a fuzzy system with multiple rule bases to solve multi-criteria decision making problems where both benefit and cost criteria are presented as subsystems. Thus, the decision maker evaluates the performance of each alternative for optimization and further observes the performance for both benefit and cost criteria. This approach improves significantly the transparency of the TOPSIS method while ensuring high effectiveness in comparison to established methods. To ensure practicality and effectiveness of the proposed method, a traded equity case study is considered. Furthermore, the ranking based on the proposed method is validated comparatively using spearman rho correlation. The proposed methodoutperforms the existing TOPSIS methods in terms of ranking for the case study under consideration.

AB - This paper introduces a novel modification of the technique for ordering of preference by similarity to ideal solution (TOPSIS) method and uses a fuzzy system with multiple rule bases to solve multi-criteria decision making problems where both benefit and cost criteria are presented as subsystems. Thus, the decision maker evaluates the performance of each alternative for optimization and further observes the performance for both benefit and cost criteria. This approach improves significantly the transparency of the TOPSIS method while ensuring high effectiveness in comparison to established methods. To ensure practicality and effectiveness of the proposed method, a traded equity case study is considered. Furthermore, the ranking based on the proposed method is validated comparatively using spearman rho correlation. The proposed methodoutperforms the existing TOPSIS methods in terms of ranking for the case study under consideration.

KW - fuzzy systems

KW - multiple rule bases

KW - TOPSIS

KW - multicriteria decision making

KW - spearman rho correlation

KW - traded equity

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M3 - Conference contribution

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BT - Proceedings of the 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE World Congress on Computational Intelligence

Y2 - 25 July 2016 through 29 July 2016

ER -

Fuzzy systems with multiple rule bases for selection of alternatives using TOPSIS

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Keywords

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