방법 비교

	데이터 기반 다기준 의사결정 분석	PROMETHEE II
분야	의사결정	의사결정
계열	MCDM	MCDM
기원 연도	2015	1986
창시자	Multiple authors	Brans, J. P., Vincke, Ph., Mareschal, B.
유형	Learning-based criteria weighting and aggregation	Preference function (net flow)
원전	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
별칭	Data-Driven MCDA	—
관련	5	8
요약	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.