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Datadrevet multi-kriterie beslutningsanalyse×PROMETHEE II×
FagområdeBeslutningstagningBeslutningstagning
FamilieMCDMMCDM
Oprindelsesår20151986
OphavspersonMultiple authorsBrans, J. P., Vincke, Ph., Mareschal, B.
TypeLearning-based criteria weighting and aggregationPreference function (net flow)
Oprindelig kildeГреченко, Д. В. (2019). Data-driven decision making: Integrating machine learning with multi-criteria approaches. Computational Statistics & Data Analysis, 132, 127-143. link ↗Brans, J. P., Vincke, Ph., Mareschal, B. (1986). How to select and how to rank projects: The PROMETHEE method. European Journal of Operational Research DOI ↗
AliasserData-Driven MCDA
Relaterede58
ResuméData-Driven MCDA is a hybrid framework that integrates machine learning and statistical learning into traditional multi-criteria decision analysis. Instead of eliciting weights from expert judgment, it learns criteria importance from historical decision data, enabling more scalable and empirically grounded decision support.PROMETHEE (PROMETHEE II — Preference Ranking Organisation METHod for Enrichment of Evaluations) is a outranking multi-criteria decision-making (MCDM) method introduced by Brans, J. P., Vincke, Ph., Mareschal, B. in 1986. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateSammenlign metoder: Data-Driven MCDA · PROMETHEE. Hentet 2026-06-15 fra https://scholargate.app/da/compare