Vertaile menetelmiä

	Data-Driven Multi-Criteria Decision Analysis	PROMETHEE II
Tieteenala	Päätöksenteko	Päätöksenteko
Menetelmäperhe	MCDM	MCDM
Syntyvuosi	2015	1986
Kehittäjä	Multiple authors	Brans, J. P., Vincke, Ph., Mareschal, B.
Tyyppi	Learning-based criteria weighting and aggregation	Preference function (net flow)
Alkuperäislähde	Греченко, Д. В. (2019). Data-driven decision making: Integrating machine learning with multi-criteria approaches. Computational Statistics & Data Analysis, 132, 127-143.	Brans, J. P., Vincke, Ph., Mareschal, B. (1986). How to select and how to rank projects: The PROMETHEE method. European Journal of Operational Research
Rinnakkaisnimet	Data-Driven MCDA	—
Liittyvät	5	8
Tiivistelmä	Data-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.