Sequential Parameter Optimization Toolbox
SPOT uses a combination statistic models and optimization algorithms for the purpose of parameter optimization. Design of Experiment methods are employed to generate an initial set of candidate solutions, which are evaluated with a user-provided objective function. The resulting data is used to fit a model, which in turn is subject to an optimization algorithm, to find the most promising candidate solution(s). These are again evaluated, after which the model is updated with the new results. This sequential procedure of modeling, optimization, and evaluation is iterated until the evaluation budget is exhausted.
Thomas Bartz-Beielstein email@example.com
Thomas Bartz-Beielstein firstname.lastname@example.org, Martin Zaefferer, and F. Rehbach with contributions from: C. Lasarczyk, M. Rebolledo, Joerg Stork.
Main interface function is
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