Adaptation of the UOBYQA algorithm for noisy functions

• Published in: Proceedings of the 38th conference on Winter simulation pp. 312 - 319
• Main Authors: Deng, Geng, Ferris, Michael C.
• Format: Conference Proceeding
• Language: English
• Published: Winter Simulation Conference 03.12.2006
• Series: ACM Conferences
• Subjects: Information systems; Information systems > Data management systems; Information systems > Data management systems > Database administration; Information systems > Data management systems > Database administration > Data dictionaries; Theory of computation; Theory of computation > Design and analysis of algorithms; Theory of computation > Design and analysis of algorithms > Mathematical optimization
• ISBN: 9781424405015; 1424405017
• DOI: 10.5555/1218112.1218173

In many real-world optimization problems, the objective function may come from a simulation evaluation so that it is (a) subject to various levels of noise, (b) not differentiable, and (c) computationally hard to evaluate. In this paper, we modify Powell's UOBYQA algorithm to handle those real-world simulation problems. Our modifications apply Bayesian techniques to guide appropriate sampling strategies to estimate the objective function. We aim to make the underlying UOBYQA algorithm proceed efficiently while simultaneously controlling the amount of computational effort.