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

Mingxia Huang, Dingguo Pu

  • 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.


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