Sammenlign metoder

	Optimering-assisteret design af eksperimenter	Box-Behnken Design
Fagområde	Forsøgsdesign	Forsøgsdesign
Familie	Process / pipeline	Process / pipeline
Oprindelsesår	1980 (desirability approach); broader integration through 1990s–2000s	1960
Ophavsperson	Derringer & Suich (desirability function); extended by Myers, Montgomery, and Anderson-Cook	George E. P. Box and Donald W. Behnken
Type	Hybrid experimental-optimization method	Response surface design (incomplete three-level factorial)
Oprindelig kilde	Derringer, G., & Suich, R. (1980). Simultaneous optimization of several response variables. Journal of Quality Technology, 12(4), 214–219.	Box, G. E. P., & Behnken, D. W. (1960). Some new three level designs for the study of quantitative variables. Technometrics, 2(4), 455–475.
Aliasser	OA-DoE, DoE with optimization, optimization-integrated DoE, multi-objective experimental optimization	BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design
Relaterede	4	3
Resumé	Optimization-assisted design of experiments (OA-DoE) couples a structured experimental plan with a mathematical optimization engine to locate factor settings that simultaneously satisfy multiple response objectives. Rather than stopping at fitting a response surface model, the analyst applies desirability functions, genetic algorithms, or other optimizers to the fitted model to identify the global or near-global optimum across all responses of interest.	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.