PMBO: Enhancing Black-Box Optimization through Multivariate Polynomial Surrogates

arXiv:2403.07485v1 Announce Type: cross
Abstract: We introduce a surrogate-based black-box optimization method, termed Polynomial-model-based optimization (PMBO). The algorithm alternates polynomial approximation with Bayesian optimization steps, using Gaussian processes to model the error between the objective and its polynomial fit. We describe the algorithmic design of PMBO and compare the results of the performance of PMBO with several optimization methods for a set of analytic test functions.
The results show that PMBO outperforms the classic Bayesian optimization and is robust with …

abstract algorithm approximation arxiv bayesian box cs.lg cs.ms design error gaussian processes math.oc multivariate optimization polynomial processes results the algorithm through type