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STRUCTURING A COMPUTATIONAL TOOL FOR DEFINING MULTICRITERIA METHODS: A PROPOSAL FOR A SYSTEMATIC LITERATURE REVIEW

David de Oliveira Costa et al.

Pesquisa Operacional2025https://doi.org/10.1590/0101-7438.2025.045.00293151article
AJG 1
Weight
0.37

What the paper says

The growing demand for a computational tool to support the selection of multicriteria decision-making (MCDM) methods, or families of methods, based on problem structuring has become a significant concern for researchers. The study addresses this need by conducting a Systematic Literature Review (SLR), which identified and stratified twenty-seven relevant papers according to four predefined research questions. This stratification clarified commonly used computational tools and their specific application to the proposed MCDM methods. Furthermore, the review revealed that existing tools are often tailored to individual methods, highlighting a gap in tools designed to recommend the appropriate MCDM or family of methods based on problem characteristics. Consequently, the SLR identified a clear opportunity for further research and the development of a computational tool that facilitates method selection based on the structured problem. This paper describes the development process, methodological framework, and refined analysis of the findings with a robust protocol for this SLR.

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https://doi.org/https://doi.org/10.1590/0101-7438.2025.045.00293151

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@article{david2025,
  title        = {{STRUCTURING A COMPUTATIONAL TOOL FOR DEFINING MULTICRITERIA METHODS: A PROPOSAL FOR A SYSTEMATIC LITERATURE REVIEW}},
  author       = {David de Oliveira Costa et al.},
  journal      = {Pesquisa Operacional},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1590/0101-7438.2025.045.00293151},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.