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...

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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
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container_title SIAM journal on scientific computing
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creator BYRD, R. H
PEIHUANG LU
NOCEDAL, J
CIYOU ZHU
description 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.
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subjects 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
title A limited memory algorithm for bound constrained optimization
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