Сравнение на методи

	Симулационно-асистирана методология на повърхността на отклика	Дизайн на Бокс-Бенкен
Област	Планиране на експеримента	Планиране на експеримента
Семейство	Process / pipeline	Process / pipeline
Година на възникване	1951 (RSM); simulation integration widely adopted from 1980s onward	1960
Създател	Box & Wilson (RSM foundation); Kleijnen and others for simulation-based extensions	George E. P. Box and Donald W. Behnken
Тип	Experimental optimization method	Response surface design (incomplete three-level factorial)
Основополагащ източник	Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2016). Response Surface Methodology: Process and Product Optimization Using Designed Experiments (4th ed.). Wiley. ISBN: 978-1118916025	Box, G. E. P., & Behnken, D. W. (1960). Some new three level designs for the study of quantitative variables. Technometrics, 2(4), 455–475.
Други названия	SA-RSM, simulation-based RSM, computer simulation RSM, metamodel-assisted RSM	BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design
Свързани	6	3
Резюме	Simulation-assisted response surface methodology (SA-RSM) combines computer simulation models — such as finite element analysis, computational fluid dynamics, or discrete-event simulation — with the statistical framework of response surface methodology to efficiently map, model, and optimize system responses. Instead of running physical experiments, the researcher executes simulation runs at design points prescribed by an RSM design, fits a polynomial metamodel (surrogate) to the simulation outputs, and uses that metamodel to locate optimal factor settings.	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.