| Texto completo | |
| Autor(es): |
Machado, Rafaela Heloisa Carvalho
;
Conceicao, Samuel Vieira
;
Pelissari, Renata
;
Santos, Arthur Almeida
;
Ben Amor, Sarah
Número total de Autores: 5
|
| Tipo de documento: | Artigo Científico |
| Fonte: | APPLIED SOFT COMPUTING; v. 180, p. 16-pg., 2025-08-01. |
| Resumo | |
A great majority of Multiple Criteria Decision Aiding (MCDA) methods assume that all assessment criteria are considered at the same hierarchical level. However, decision problems often involve hierarchical structures with varying configurations. Another common challenge in real-world decision-making is the perceived subjectivity of preference elicitation. Although these challenges have been widely discussed in the literature, they have not been adequately addressed in the context of the VIKOR method. This paper proposes a new VIKOR-based method, called VIKOR-HSMAA, that deals simultaneously with indirect preference elicitation and hierarchical structure of criteria. The novelty of the methodology consists of a joint consideration of hierarchical assessments of alternatives performances for hierarchical criteria, considering imprecise criteria weights and analysis of compromise solution resulting from the VIKOR method. In addition, the conditions for the acceptance of VIKOR's solution are adapted as new SMAA descriptive measures. A case study regarding the assessment of sustainability dimensions of Brazilian states shows the method application. VIKOR-HSMAA provided information at the sustainability level with the state of Santa Catarina (SC) as the most sustainable. Considering each macro-criterion, SC is the first in the economic dimension, Roraima and Distrito Federal (DF) are the two first in the environmental rank and SC and DF are the two first in the social rank. By enabling the consideration of missing or imprecise data, the VIKOR-HSMAA method proves to be a robust tool to reduce subjectivity in decision-making, providing a reliable support system for the assessment of institutions and governments. VIKOR-HSMAA innovates by providing stochastic measures to consider more than one alternative in the solution, thus maintaining the characteristics and advantages of the VIKOR method in a structure with imprecise data and hierarchy of criteria. (AU) | |
| Processo FAPESP: | 24/18109-3 - Equidade em problemas de classificação multicritério |
| Beneficiário: | Renata Pelissari Infante |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |
| Processo FAPESP: | 24/05971-9 - 33rd European Conference on Operational Research |
| Beneficiário: | Renata Pelissari Infante |
| Modalidade de apoio: | Auxílio à Pesquisa - Reunião - Exterior |
| Processo FAPESP: | 20/09838-0 - BI0S - Brazilian Institute of Data Science |
| Beneficiário: | João Marcos Travassos Romano |
| Modalidade de apoio: | Auxílio à Pesquisa - Programa Centros de Pesquisa Aplicada |