Yaakob, Abdul Malek and Gegov, Alexander and Abdul Rahman, Siti Fatimah (2017) Selection of alternatives using fuzzy networks with rule base aggregation. Fuzzy Sets and Systems. ISSN 0165-0114

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Abstract

This paper introduces a novel extension of the Technique for Ordering of Preference by Similarity to Ideal Solution (TOPSIS) method. The method is based on aggregation of rules with different linguistic of the output of fuzzy networks to solve multi-criteria decision-making problems whereby both benefit and cost criteria are presented as subsystems. Thus the decision maker evaluates the performance of each alternative for decision process and further observes the performance for both benefit and cost criteria. The aggregation sub-stage in a fuzzy system maps the fuzzy membership functions for all rules to an aggregated fuzzy membership function representing the overall output for the rules. This approach improves significantly the transparency of the TOPSIS methods, while ensuring high effectiveness in comparison to established approaches. To ensure practicality and effectiveness, the proposed method is further tested on portfolio selection problems. The ranking produced by the method is comparatively validated using Spearman rho rank correlation. The results show that the proposed method outperforms the existing TOPSIS approaches in term of ranking performance.

Item Type:	Article
Uncontrolled Keywords:	TOPSIS; Fuzzy networks; Selection alternatives; Fuzzy sets; Interval type 2 fuzzy sets; Z-numbers; Stock selection; Spearman rho; Type 1 fuzzy sets
Subjects:	Q Science > QA Mathematics
Divisions:	School of Quantitative Sciences
Depositing User:	Mr. Abdul Malek Yaakob
Date Deposited:	18 Sep 2017 00:12
Last Modified:	18 Sep 2017 00:12
URI:	https://repo.uum.edu.my/id/eprint/22926

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