Confronta i metodi

	Analisi multicriterio basata sui dati	ELECTRE I	PROMETHEE II
Campo	Processo decisionale	Processo decisionale	Processo decisionale
Famiglia	MCDM	MCDM	MCDM
Anno di origine	2015	1968	1986
Ideatore	Multiple authors	Roy, B.	Brans, J. P., Vincke, Ph., Mareschal, B.
Tipo	Learning-based criteria weighting and aggregation	Concordance–discordance (crisp outranking)	Preference function (net flow)
Fonte seminale	Греченко, Д. В. (2019). Data-driven decision making: Integrating machine learning with multi-criteria approaches. Computational Statistics & Data Analysis, 132, 127-143.	Roy, B. (1968). Classement et choix en présence de points de vue multiples (la méthode ELECTRE). Revue Française d'Informatique et de Recherche Opérationnelle	Brans, J. P., Vincke, Ph., Mareschal, B. (1986). How to select and how to rank projects: The PROMETHEE method. European Journal of Operational Research
Alias	Data-Driven MCDA	—	—
Correlati	5	8	8
Sintesi	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.	ELECTRE (ELECTRE I — ELimination Et Choix Traduisant la REalité) is a outranking multi-criteria decision-making (MCDM) method introduced by Roy, B. in 1968. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	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.