A restoration-free filter SQP algorithm for equality constrained optimization

In this paper, a trust-region sequential quadratic programming algorithm with a modified filter acceptance mechanism is proposed for nonlinear equality constrained optimization. The most important advantage of the proposed algorithm is its avoidance of any feasibility restoration phase, a necessity...

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Veröffentlicht in:Applied mathematics and computation Jg. 219; H. 11; S. 6016 - 6029
Hauptverfasser: Zhu, Xiaojing, Pu, Dingguo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Inc 01.02.2013
Schlagworte:
Algorithms
Constrained optimization
Constraints
Convergence
Feasibility
Feasibility restoration
Filter
Mathematical models
Optimization
Quadratic programming
Sequential quadratic programming
Feasibility restoration
Sequential quadratic programming
Filter
Constrained optimization
ISSN:0096-3003, 1873-5649
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:In this paper, a trust-region sequential quadratic programming algorithm with a modified filter acceptance mechanism is proposed for nonlinear equality constrained optimization. The most important advantage of the proposed algorithm is its avoidance of any feasibility restoration phase, a necessity in traditional filter methods. We solve quadratic programming subproblems based on the well-known Byrd–Omojokun trust-region method. Inexact solutions to these subproblems are allowed. Under some standard assumptions, global convergence of the proposed algorithm is established. Numerical results show our approach is potentially useful.
Bibliographie:ObjectType-Article-2
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ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2012.12.002