Global Optimization for Noisy Expensive Black-Box Multi-Modal Functions Via Radial Basis Function Surrogate

• Published in: Proceedings - Winter Simulation Conference pp. 3020 - 3031
• Main Authors: Shen, Yichi, Shoemaker, Christine A.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.12.2020
• Subjects: Approximation algorithms; Fitting; Inference algorithms; Noise measurement; Optimization; Reliability; Response surface methodology

This study proposes a new surrogate global optimization algorithm that solves problems with expensive black-box multi-modal objective functions subject to homogeneous evaluation noise. Specifically, we propose a new radial basis function (RBF) surrogate to approximate noisy functions and extend the...