A limited memory algorithm for bound constrained optimization

A limited memory algorithm for bound constrained optimization

An algorithm for solving large nonlinear optimization problems with simple bounds is described. It is based on the gradient projection method and uses a limited memory BFGS matrix to approximate the Hessian of the objective function. It is shown how to take advantage of the form of the limited memor...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:SIAM journal on scientific computing 1995-09, Vol.16 (5), p.1190-1208
Hauptverfasser: BYRD, R. H, PEIHUANG LU, NOCEDAL, J, CIYOU ZHU
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Applied sciences
Approximation
Calculus of variations and optimal control
Computer science
Exact sciences and technology
Grants
Mathematical analysis
Mathematics
Operational research and scientific management
Operational research. Management science
Optimization
Optimization. Search problems
Sciences and techniques of general use
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:An algorithm for solving large nonlinear optimization problems with simple bounds is described. It is based on the gradient projection method and uses a limited memory BFGS matrix to approximate the Hessian of the objective function. It is shown how to take advantage of the form of the limited memory approximation to implement the algorithm efficiently. The results of numerical tests on a set of large problems are reported.
ISSN:1064-8275
1095-7197
DOI:10.1137/0916069