Nonmonotone adaptive trust-region method for unconstrained optimization problems

In this paper, an adaptive trust region method with nonmonotone technique for unconstrained optimization problems is presented and analyzed. The global and local convergence results of the algorithm are established. Numerical results show that the new method is efficient.

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Bibliographische Detailangaben
Veröffentlicht in:	Applied mathematics and computation Jg. 163; H. 1; S. 489 - 504
Hauptverfasser:	Fu, Jinhua, Sun, Wenyu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY Elsevier Inc 05.04.2005 Elsevier
Schlagworte:	Calculus of variations and optimal control Exact sciences and technology Global convergence Mathematical analysis Mathematics Nonmonotone methods Numerical analysis Numerical analysis. Scientific computation Numerical methods in mathematical programming, optimization and calculus of variations Sciences and techniques of general use Superlinear convergence Trust region method Unconstrained optimization Superlinear convergence Global convergence Unconstrained optimization Nonmonotone methods Trust region method Numerical analysis Applied mathematics Optimization method Algorithm Adaptive method Convergence Mathematical programming
ISSN:	0096-3003, 1873-5649
Online-Zugang:	Volltext
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