Journal of applied mathematics & informatics

The Korean Society for Computational and Applied Mathematics (한국전산응용수학회)
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A GLOBALLY AND SUPERLIEARLY CONVERGENT FEASIBLE SQP ALGORITHM FOR DEGENERATE CONSTRAINED OPTIMIZATION

  • Received : 2009.08.29
  • Accepted : 2009.10.07
  • Published : 2010.05.30
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Abstract

In this paper, A FSQP algorithm for degenerate inequality constraints optimization problems is proposed. At each iteration of the proposed algorithm, a feasible direction of descent is obtained by solving a quadratic programming subproblem. To overcome the Maratos effect, a higher-order correction direction is obtained by solving another quadratic programming subproblem. The algorithm is proved to be globally convergent and superlinearly convergent under some mild conditions. Finally, some preliminary numerical results are reported.

Keywords

References

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