Comparer des méthodes

	Planification centrale composite assistée par optimisation	Plan de Box-Behnken
Domaine	Plans d'expériences	Plans d'expériences
Famille	Process / pipeline	Process / pipeline
Année d'origine	1951 (CCD); optimization coupling formalized 1970s–1990s	1960
Auteur d'origine	Box & Wilson (CCD, 1951); optimization integration by Myers, Montgomery & colleagues	George E. P. Box and Donald W. Behnken
Type	Experimental design with mathematical optimization	Response surface design (incomplete three-level factorial)
Source fondatrice	Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2009). Response Surface Methodology: Process and Product Optimization Using Designed Experiments (3rd ed.). Wiley. ISBN: 978-0470174463	Box, G. E. P., & Behnken, D. W. (1960). Some new three level designs for the study of quantitative variables. Technometrics, 2(4), 455–475.
Alias	CCD with optimization, optimized CCD, RSM-CCD optimization, central composite design with response optimization	BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design
Apparentées	3	3
Résumé	Optimization-assisted central composite design (CCD) combines the rotatable, second-order experimental layout of central composite design with mathematical optimization algorithms — typically desirability functions, response surface optimization, or metaheuristics — to find the factor settings that simultaneously maximize, minimize, or hit target values for one or more response variables. It is the most widely applied response-surface optimization workflow in chemical, pharmaceutical, food science, and manufacturing engineering.	The Box-Behnken design (BBD) is an efficient response surface methodology design that fits a full second-order polynomial model using three levels of each factor. Introduced by Box and Behnken in 1960, it places experimental points at the midpoints of the edges of a hypercube and at the center, avoiding the corner points where all factors are simultaneously at their extreme levels. This structure makes BBD particularly attractive when extreme-level combinations are physically impossible, costly, or unsafe to test.