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Volume 21, Issue 2
A Trust-Region Algorithm for Nonlinear Inequality Constrained Optimization

Xiaojiao Tong & Shuzi Zhou

J. Comp. Math., 21 (2003), pp. 207-220.

Published online: 2003-04

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  • 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.

  • Keywords

Inequality constrained optimization, Trust-region method, Global convergence, Local quadratic convergence.

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COPYRIGHT: © Global Science Press

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@Article{JCM-21-207, author = {}, title = {A Trust-Region Algorithm for Nonlinear Inequality Constrained Optimization}, journal = {Journal of Computational Mathematics}, year = {2003}, volume = {21}, number = {2}, pages = {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.

}, issn = {1991-7139}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jcm/10275.html} }
TY - JOUR T1 - A Trust-Region Algorithm for Nonlinear Inequality Constrained Optimization JO - Journal of Computational Mathematics VL - 2 SP - 207 EP - 220 PY - 2003 DA - 2003/04 SN - 21 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jcm/10275.html KW - Inequality constrained optimization, Trust-region method, Global convergence, Local quadratic convergence. AB -

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.

Xiaojiao Tong & Shuzi Zhou. (1970). A Trust-Region Algorithm for Nonlinear Inequality Constrained Optimization. Journal of Computational Mathematics. 21 (2). 207-220. doi:
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