Comparer des méthodes

	Planification expérimentale optimale (D-optimale, I-optimale)	Planification Composite Centrale
Domaine	Plans d'expériences	Plans d'expériences
Famille	Hypothesis test	Process / pipeline
Année d'origine	1972	1951
Auteur d'origine	V. V. Fedorov	George E. P. Box and K. B. Wilson
Type	Computer-aided optimal design	Response surface experimental design
Source fondatrice	Fedorov, V.V. (1972). Theory of Optimal Experiments. Academic Press.	Box, G. E. P., & Wilson, K. B. (1951). On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society: Series B, 13(1), 1–45.
Alias	D-Optimal Design, I-Optimal Design, Computer-Generated Design, Optimal Deneme Deseni (D-Optimal, I-Optimal)	CCD, Box-Wilson design, central composite response surface design, rotatable central composite design
Apparentées	5	3
Résumé	Optimal experimental design is a computer-aided approach to constructing experiments that maximises statistical efficiency for a given model and run budget. Formalised by V. V. Fedorov in 1972, it selects experimental points from a candidate set so that the information matrix M = X'X is optimised according to a chosen criterion — most commonly D-optimality (maximising the determinant) or I-optimality (minimising average prediction variance). It is the preferred strategy whenever classical designs such as central composite or Box-Behnken cannot be applied because the experimental region is constrained or factor ranges are irregular.	Central Composite Design (CCD) is a second-order response surface design that allows researchers to efficiently fit a full quadratic model relating multiple continuous input factors to one or more response variables. Introduced by Box and Wilson in 1951, it combines a factorial (or fractional factorial) core, axial (star) points, and center-point replicates into a single unified design, making it the most widely used design for process optimization in engineering, chemistry, and manufacturing.