Surrogate-assisted evolutionary programming for high dimensional constrained black-box optimization

Authors:
Rommel G. Regis
Affiliations:
Saint Joseph's University, Philadelphia, PA, USA
Venue:
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Year:
2012

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Abstract

This paper presents a novel surrogate-assisted evolutionary programming (EP) method for high dimensional constrained black-box optimization with many black-box inequality constraints. A cubic radial basis function (RBF) surrogate is used and the resulting RBF-assisted EP outperforms a standard EP, an RBF-assisted penalty-based EP, Stochastic Ranking Evolution Strategy and Scatter Search on a 124-D automotive problem with 68 black-box constraints.