A nonmonotone trust region method based on simple conic models for unconstrained optimization

A new nonmonotone trust region algorithm with simple conic models for unconstrained optimization is proposed. Compared to traditional conic trust region methods, the new method needs less memory capacitance and computational complexity. The global convergence and fast local convergence rate of the p...

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Veröffentlicht in:	Applied mathematics and computation 2013-12, Vol.225, p.295-305
Hauptverfasser:	Zhou, Qunyan, Zhou, Fen, Cao, Fengxue
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Capacitance Computation Conics Convergence Global convergence Mathematical analysis Mathematical models Nonmonotone trust region method Optimization Simple conic model Unconstrained optimization
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