Paper Info
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 method outperforms the existing TOPSIS methods in terms of ranking for the case study under consideration.
Year
Venue
Keywords
2016
2016 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE)
fuzzy systems, multiple rule bases, TOPSIS, multi-criteria decision making, spearman rho correlation, Traded equity
Field
DocType
ISSN
Data mining,Mathematical optimization,Ranking,Computer science,Ideal solution,Fuzzy set,TOPSIS,Fuzzy control system,Spearman's rank correlation coefficient,Decision maker
Conference
1544-5615
Citations 
PageRank 
References 
2
0.37
10
Authors
4
Name
Order
Citations
PageRank
Abdul Malek Yaakob1211.70
Alexander E. Gegov2478.47
Mohamed Bahy Bader-El-Den312614.16
Siti Fatimah Abdul Rahman420.71