![]() The present study aimed at evaluating the performance characteristics of various surrogate models depending on the Latin hypercube sampling (LHS) procedure (sample size and spatial distribution) for a diverse set of optimization problems. The exploration/exploitation properties of surrogate models depend on the size and distribution of design points in the chosen design space. Latin hypercube sampling is widely used design-of-experiment technique to select design points for simulation which are then used to construct a surrogate model.
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