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

Mingxia Huang ^[1] ; Dingguo Pu ^[2]
1. [1] Tongji University
  
  Tongji University
  
  China
2. [2] Henan University of Science and Technology
  
  Henan University of Science and Technology
  
  China
Localización: Journal of computational and applied mathematics, ISSN 0377-0427, Vol. 281, Nº 1 (June 2015), 2015, págs. 107-119
Idioma: inglés
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Resumen
- 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.