Remark on "algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound constrained optimization"

José Luis Morales; Jorge Nocedal

doi:10.1145/2049662.2049669

Remark on "algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound constrained optimization"

José Luis Morales^*, Jorge Nocedal

^*Corresponding author for this work

Industrial Engineering and Management Sciences

Research output: Contribution to journal › Article › peer-review

273 Scopus citations

Abstract

This remark describes an improvement and a correction to Algorithm 778. It is shown that the performance of the algorithm can be improved significantly by making a relatively simple modification to the subspace minimization phase. The correction concerns an error caused by the use of routine dpmeps to estimate machine precision.

Original language	English (US)
Article number	7
Journal	ACM Transactions on Mathematical Software
Volume	38
Issue number	1
DOIs	https://doi.org/10.1145/2049662.2049669
State	Published - Nov 1 2011

Keywords

Constrained optimization
Infeasibility
Nonlinear programming

ASJC Scopus subject areas

Software
Applied Mathematics

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10.1145/2049662.2049669

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keywords = "Constrained optimization, Infeasibility, Nonlinear programming",

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N2 - This remark describes an improvement and a correction to Algorithm 778. It is shown that the performance of the algorithm can be improved significantly by making a relatively simple modification to the subspace minimization phase. The correction concerns an error caused by the use of routine dpmeps to estimate machine precision.

AB - This remark describes an improvement and a correction to Algorithm 778. It is shown that the performance of the algorithm can be improved significantly by making a relatively simple modification to the subspace minimization phase. The correction concerns an error caused by the use of routine dpmeps to estimate machine precision.

KW - Constrained optimization

KW - Infeasibility

KW - Nonlinear programming

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Remark on "algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound constrained optimization"

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

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