方法证据记录
Optimization-assisted fractional factorial design
Optimization-assisted fractional factorial design (OA-FFD) combines classical fractional factorial screening with algorithmic optimality criteria — such as D-, I-, or A-optimality — to construct experiment matrices that maximize statistical efficiency. Instead of relying solely on standard orthogonal-array tables, a computer algorithm selects the best subset of runs from a candidate set, enabling experimenters to handle irregular factor constraints, mixed factor types, and custom run sizes that standard tables cannot accommodate.
源记录
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Optimization-Assisted Fractional Factorial Design
分类方法记录 · process-pipeline / experimental-design
- Atkinson, A. C., Donev, A. N., & Tobias, R. D. (2007). Optimum Experimental Designs, with SAS. Oxford University Press. · ISBN 978-0199296606
- Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. · ISBN 978-1119320937
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