Authors:
Jonata C. Wieczynski
1
;
Giancarlo Lucca
1
;
2
;
Eduardo N. Borges
1
;
Graçaliz P. Dimuro
3
;
4
;
Rodolfo Lourenzutti
3
and
Humberto Bustince
5
Affiliations:
1
Programa de Pos-Graduação em Computação, Universidade Federal do Rio Grande, Av. Itália Km 8, Rio Grande, Brazil
;
2
Programa de Pós-Graduação em Modelagem Computacional, Universidade Federal do Rio Grande, Rio Grande, Brazil
;
3
Department of Statistics, University of British Columbia, Vancouver, Canada
;
4
Programa de Pós-Graduação em Computação, Universidade Federal do Rio Grande, Av. Itália km 8, Rio Grande, Brazil
;
5
Departamento de Estadística, Informática y Matemáticas, Universidad Publica de Navarra, Pamplona, Spain
Keyword(s):
Decision Making, TOPSIS, GMC-RTOPSIS, Generalized Choquet Integral, CC-integrals.
Abstract:
In business, one of the most important management functions is decision making. The Group Modular Choquet Random TOPSIS (GMC-RTOPSIS) is a Multi-Criteria Decision Making (MCDM) method that can work with multiple heterogeneous data types. This method uses the Choquet integral to deal with the interaction between different criteria. The Choquet integral has been generalized and applied in various fields of study, such as imaging processing, brain-computer interface, and classification problems. By generalizing the so-called extended Choquet integral by copulas, the concept of CC-integrals has been introduced, presenting satisfactory results when used to aggregate the information in Fuzzy Rule-Based Classification Systems. Taking this into consideration, in this paper, we applied 11 different CC-integrals in the GMC-RTOPSIS. The results demonstrated that this approach has the advantage of allowing more flexibility and certainty in the choosing process by giving a higher separation betwe
en the first and second-ranked alternatives.
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