A sequential equality constrained quadratic programming algorithm for inequality constrained optimization

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 const...

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Veröffentlicht in:Journal of computational and applied mathematics Jg. 212; H. 1; S. 112 - 125
1. Verfasser: Zhu, Zhibin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 15.02.2008
Elsevier
Schlagworte:
Algebra
Algebraic geometry
Calculus of variations and optimal control
Equality constrained quadratical programming
Exact sciences and technology
Global convergence
Inequality constrained optimization
Mathematical analysis
Mathematics
Numerical analysis
Numerical analysis. Scientific computation
Numerical linear algebra
Numerical methods in mathematical programming, optimization and calculus of variations
Sciences and techniques of general use
SQP method
Superlinear convergence rate
Global convergence
65K05
90C30
90C55
Superlinear convergence rate
Equality constrained quadratical programming
SQP method
Inequality constrained optimization
65K05; 90C30; 90C55
Convergence acceleration
Numerical linear algebra
Optimization method
Linear programming
Iteration
Inequality constrained optimization; SQP method; Equality constrained quadratical programming; Global convergence; Superlinear convergence rate
Quadratic programming
Algorithm
Convergence
Constrained optimization
Equation system
Direct method
Numerical analysis
Linear system
Linear equation
Matrix inversion
Applied mathematics
Sequential method
Convergence rate
Mathematical programming
ISSN:0377-0427, 1879-1778
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung: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.
Bibliographie:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0377-0427
1879-1778
DOI:10.1016/j.cam.2006.11.028