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LANS Publications

"A Trust-Region Algorithm for Global Optimization"

B. Addis and S. Leyffer

Preprint ANL/MCS-P1190-0804

Preprint Version: [pdf]

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.