-

 

 

 




Optimization Online





 

A Trust-Region Algorithm for Global Optimization

Bernardetta Addis (b.addis***at***ing.unifi.it)
Sven Leyffer (leyffer***at***mcs.anl.gov)

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.

Keywords: Global optimization, smoothing, trust region

Category 1: Global Optimization (Stochastic Approaches )

Citation: Mathematics and Computer Science Division Preprint ANL/MCS-P1190-0804, Argonne National Laboratory, Argonne, IL, August 2004

Download: [Postscript][PDF]

Entry Submitted: 08/06/2004
Entry Accepted: 08/06/2004
Entry Last Modified: 08/13/2004

Modify/Update this entry


  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository

 

Submit
Update
Policies
Coordinator's Board
Classification Scheme
Credits
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Programming Society