A TRUST REGION SUBSPACE METHOD FOR LARGE-SCALE UNCONSTRAINED OPTIMIZATION

This paper presents a trust region subspace method for minimizing large-scale unconstrained problems. We choose a subspace that consists of some old directions which are invariable and some newest directions which are changed at each iteration. A restart technique is used when the old directions have little contribution. Numerical results are reported which indicate that the method is promising.

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Year of publication:	2012
Authors:	GONG, LUJIN
Published in:	Asia-Pacific Journal of Operational Research (APJOR). - World Scientific Publishing Co. Pte. Ltd., ISSN 1793-7019. - Vol. 29.2012, 04, p. 1250021-1
Publisher:	World Scientific Publishing Co. Pte. Ltd.
Subject:	Large scale \| unconstrained optimization \| subspace method \| trust region

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Extent:	application/pdf text/html
Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010567099