A sequential equality constrained quadratic programming algorithm for inequality constrained optimization

Authors:
Zhibin Zhu
Affiliations:
Department of Computational Science and Mathematics, Guilin University of Electronic Technology, Guilin 541004, PR China
Venue:
Journal of Computational and Applied Mathematics
Year:
2008

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Abstract

In this paper, the feasible type SQP method is improved. A new SQP algorithm is presented to solve the nonlinear inequality constrained optimization. As compared with the existing SQP methods, per single iteration, in order to obtain the search direction, it is only necessary to solve equality constrained quadratic programming subproblems and systems of linear equations. Under some suitable conditions, the global and superlinear convergence can be induced.