Year: 2003
Journal of Computational Mathematics, Vol. 21 (2003), Iss. 2 : pp. 207–220
Abstract
This paper presents a new trust-region algorithm for $n$-dimension nonlinear optimization subject to $m$ nonlinear inequality constraints. Equivalent KKT conditions are derived, which is the basis for constructing the new algorithm. Global convergence of the trial steps, local quadratic convergence theorem is proved for nondegenerate minimizer point. Numerical experiment is presented to show the effectiveness of our approach.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2003-JCM-10275
Journal of Computational Mathematics, Vol. 21 (2003), Iss. 2 : pp. 207–220
Published online: 2003-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 14
Keywords: Inequality constrained optimization Trust-region method Global convergence Local quadratic convergence.