Application of independent component analysis and TOPSIS to deal with dependent criteria in multicriteria decision problems

Autor(es)

Pelegrina, Guilherme Dean ^[1] ; Duarte, Leonardo Tomazeli ^[2] ; Travassos Romano, Joao Marcos ^[1]

Afiliação do(s) autor(es)

^[1] Univ Campinas UNICAMP, Sch Elect & Comp Engn FEEC, Campinas, SP - Brazil

^[2] Univ Campinas UNICAMP, Sch Appl Sci FCA, Limeira - Brazil

• Tipo de documento: Artigo Científico
• Fonte: EXPERT SYSTEMS WITH APPLICATIONS; v. 122, p. 262-280, MAY 15 2019.
• Citações Web of Science: 2

Resumo

A vast number of multicriteria decision making methods have been developed to deal with the problem of ranking a set of alternatives evaluated in a multicriteria fashion. Very often, these methods assume that the evaluation among criteria is statistically independent. However, in actual problems, the observed data may comprise dependent criteria, which, among other problems, may result in biased rankings. In order to deal with this issue, we propose a novel approach whose aim is to estimate, from the observed data, a set of independent latent criteria, which can be seen as an alternative representation of the original decision matrix. A central element of our approach is to formulate the decision problem as a blind source separation problem, which allows us to apply independent component analysis techniques to estimate the latent criteria. Moreover, we consider TOPSIS-based approaches to obtain the ranking of alternatives from the latent criteria. Results in both synthetic and actual data attest the relevance of the proposed approach. (C) 2019 Elsevier Ltd. All rights reserved. (AU)

• Processo FAPESP: 17/23879-9 - Integrais de Choquet em tomada de decisão multicritério multigrupo
• Beneficiário: Guilherme Dean Pelegrina
• Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Doutorado
• Processo FAPESP: 16/21571-4 - Métodos de apoio à decisão multicritério e multigrupo: modelos baseados no processamento da informação
• Beneficiário: Guilherme Dean Pelegrina
• Modalidade de apoio: Bolsas no Brasil - Doutorado