Muticriteria Decision Making Based on Independent Component Analysis: A Preliminary Investigation Considering the TOPSIS Approach

Autor(es)

Pelegrina, Guilherme Dean ; Duarte, Leonardo Tomazeli ; Travassos Romano, Joao Marcos ; Deville, Y ; Gannot, S ; Mason, R ; Plumbley, MD ; Ward, D

• Tipo de documento: Artigo Científico
• Fonte: LATENT VARIABLE ANALYSIS AND SIGNAL SEPARATION (LVA/ICA 2018); v. 10891, p. 10-pg., 2018-01-01.

Resumo

This work proposes the application of independent component analysis to the problem of ranking different alternatives by considering criteria that are not necessarily statistically independent. In this case, the observed data (the criteria values for all alternatives) can be modeled as mixtures of latent variables. Therefore, in the proposed approach, we perform ranking by means of the TOPSIS approach and based on the independent components extracted from the collected decision data. Numerical experiments attest the usefulness of the proposed approach, as they show that working with latent variables leads to better results compared to already existing methods. (AU)

• 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
• 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