A trust-region SQP method without a penalty or a filter for nonlinear programming

In this paper we present a new trust-region SQP algorithm for nonlinear programming. This method avoids using a penalty function, nor a filter, and instead establishes a new step acceptance mechanism. Under some reasonable assumptions, the method can be proved to be globally convergent to a KT point...

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Bibliographic Details
Published in:Journal of computational and applied mathematics 2015-06, Vol.281, p.107-119
Main Authors: Huang, Mingxia, Pu, Dingguo
Format: Article
Language:English
Subjects:
Global convergence
Nonlinear programming
SQP
Trust-region
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Summary:In this paper we present a new trust-region SQP algorithm for nonlinear programming. This method avoids using a penalty function, nor a filter, and instead establishes a new step acceptance mechanism. Under some reasonable assumptions, the method can be proved to be globally convergent to a KT point. Preliminary numerical experiments are presented that show the potential efficiency of the new approach.
ISSN:0377-0427
1879-1778
DOI:10.1016/j.cam.2014.12.021