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
• DOI: 10.1016/j.cam.2014.12.021
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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.