A nonmonotone SQP-filter method for equality constrained optimization

In this paper, we propose a nonmonotone sequential quadratic programming-filter method for solving nonlinear equality constrained optimization. This new method has more flexibility for the acceptance of the trial step and requires less computational costs compared with the monotone methods. Under re...

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Veröffentlicht in:International journal of computer mathematics Jg. 87; H. 15; S. 3489 - 3506
Hauptverfasser: Gu, Chao, Zhu, Detong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Abingdon Taylor & Francis 01.12.2010
Taylor & Francis Ltd
Schlagworte:
Acceptance
Algorithms
Computational efficiency
Computational mathematics
Computer simulation
Constraints
Convergence
filter method
Flexibility
line search
Maratos effect
Mathematical models
Nonlinear equations
nonmonotone
Optimization
Optimization algorithms
ISSN:0020-7160, 1029-0265
Online-Zugang:Volltext
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Zusammenfassung:In this paper, we propose a nonmonotone sequential quadratic programming-filter method for solving nonlinear equality constrained optimization. This new method has more flexibility for the acceptance of the trial step and requires less computational costs compared with the monotone methods. Under reasonable conditions, we give the global convergence properties. Further, the second-order correction step and nonmonotone reduction conditions are used to overcome Maratos effect so that quadratic local convergence is achieved. The numerical experiments are reported to show the effectiveness of the proposed algorithm.
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ISSN:0020-7160
1029-0265
DOI:10.1080/00207160903124942