So sánh phương pháp

	Phân tích Quyết định Đa Tiêu Chí Hướng Dữ Liệu	ELECTRE I	Simple Additive Weighting
Lĩnh vực	Ra quyết định	Ra quyết định	Ra quyết định
Họ	MCDM	MCDM	MCDM
Năm ra đời	2015	1968	1967
Người khởi xướng	Multiple authors	Roy, B.	Fishburn, P. C.
Loại	Learning-based criteria weighting and aggregation	Concordance–discordance (crisp outranking)	Additive utility (linear)
Công trình gốc	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	Fishburn, P. C. (1967). Additive utilities with incomplete product sets: Application to priorities and assignments. Operations Research
Tên gọi khác	Data-Driven MCDA	—	—
Liên quan	5	8	8
Tóm tắt	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.	SAW (Simple Additive Weighting) is a ranking multi-criteria decision-making (MCDM) method introduced by Fishburn, P. C. in 1967. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.