Please use this identifier to cite or link to this item:
Type: Artigo de periódico
Title: Algorithm 813: SPG - Software for convex-constrained optimization
Author: Birgin, EG
Martinez, JM
Raydan, M
Abstract: Fortran 77 software implementing the SPG method is introduced. SPG is a nonmonotone projected gradient algorithm for solving large-scale convex-constrained optimization problems. It combines the classical projected gradient method with the spectral gradient choice of steplength and a nonmonotone line-search strategy. The user provides objective function and gradient values, and projections onto the feasible set. Some recent numerical tests are reported on very large location problems, indicating that SPG is substantially more efficient than existing general-purpose software on problems for which projections can be computed efficiently.
Subject: algorithms
bound constrained problems
large-scale problems
nonmonotone line search
projected gradients
spectral gradient method
Country: EUA
Editor: Assoc Computing Machinery
Rights: fechado
Identifier DOI: 10.1145/502800.502803
Date Issue: 2001
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

Files in This Item:
File Description SizeFormat 
WOS000173589000003.pdf115.49 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.