Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/31052
Title: A globally and superlinearly convergent SQP algorithm for nonlinear constrained optimization
Authors: Qi, L 
Yang, YF
Keywords: Constrained optimization
Exact penalty function
Global convergence
SQP method
Superlinear convergence
Issue Date: 2001
Publisher: Kluwer Academic Publ
Source: Journal of global optimization, 2001, v. 21, no. 2, p. 157-184 How to cite?
Journal: Journal of global optimization 
Abstract: Based on a continuously differentiable exact penalty function and a regularization technique for dealing with the inconsistency of subproblems in the SQP method, we present a new SQP algorithm for nonlinear constrained optimization problems. The proposed algorithm incorporates automatic adjustment rules for the choice of the parameters and makes use of an approximate directional derivative of the merit function to avoid the need to evaluate second order derivatives of the problem functions. Under mild assumptions the algorithm is proved to be globally convergent, and in particular the superlinear convergence rate is established without assuming that the strict complementarity condition at the solution holds. Numerical results reported show that the proposed algorithm is promising.
URI: http://hdl.handle.net/10397/31052
ISSN: 0925-5001
EISSN: 1573-2916
DOI: 10.1023/A:1011983130559
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