A Trust-Region Algorithm for Global Optimization

Authors:
Bernardetta Addis;Sven Leyffer
Affiliations:
Dipartimento Sistemi e Informatica, Università di Firenze, Firenze, Italy 50129;Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, USA 60439
Venue:
Computational Optimization and Applications
Year:
2006

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Abstract

We consider the global minimization of a bound-constrained function with a so-called funnel structure. We develop a two-phase procedure that uses sampling, local optimization, and Gaussian smoothing to construct a smooth model of the underlying funnel. The procedure is embedded in a trust-region framework that avoids the pitfalls of a fixed sampling radius. We present a numerical comparison to three popular methods and show that the new algorithm is robust and uses up to 20 times fewer local minimizations steps.