Catatan bukti metode

Surrogate-Based Optimization

Surrogate-based optimization, formalized in the computer-experiments framework of Sacks et al. (1989) and popularized for engineering by Forrester et al. (2008), replaces a prohibitively expensive simulation or physical experiment with a cheap approximate model — called a surrogate or metamodel — and then optimizes that surrogate instead. The surrogate is typically a Kriging (Gaussian Process), Radial Basis Function, or polynomial response surface fitted to a small set of carefully chosen design evaluations and periodically updated as the search progresses.

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Surrogate-Based Optimization (Metamodel-Assisted Optimization)

Catatan metode taksonomi · process-pipeline / optimization

Buka metode lengkap

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Same method familyBayesian Optimizationmachine-suggested · Relational suggestion, not evidence.Same method familyDesign of experimentsmachine-suggested · Relational suggestion, not evidence.Same method familyEvolutionary Strategymachine-suggested · Relational suggestion, not evidence.Same method familyLatin Hypercube Samplingmachine-suggested · Relational suggestion, not evidence.See alsoResponse Surface Methodologymachine-suggested · Relational suggestion, not evidence.