A robust trust region method for general constrained optimization

In this paper, a new trust region method is presented for general constrained optimization problem. In this algorithm, the trial step is obtained by solving two quadratic programming problems with bound constraints. The algorithm is implementable easily. Then we prove that the method is globally convergent without regularity assumptions. Preliminary numerical experiments show the efficiency of the algorithm. Copyright Springer-Verlag 2004

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Year of publication:	2004
Authors:	Zhang, Ju-liang
Published in:	Computational Statistics. - Springer. - Vol. 60.2004, 1, p. 73-85
Publisher:	Springer
Subject:	General constrained optimization \| Global convergence \| Trust region method \| Nonlinear programming \| Regularity condition

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010759241