Algorithm 813:: SPG -: Software for convex-constrained optimization

被引:199
作者
Birgin, EG
Martínez, JM
Raydan, M
机构
[1] Univ Sao Paulo, Dept Ciencia Comp, Inst Matemat & Estatist, BR-05508900 Sao Paulo, Brazil
[2] Univ Estadual Campinas, Dept Matemat Aplicada, Inst Matemat Estatist & Comp Cient, BR-13081970 Campinas, SP, Brazil
[3] Cent Univ Venezuela, Dept Computac, Fac Ciencias, Caracas 1041A, Venezuela
来源
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE | 2001年 / 27卷 / 03期
关键词
algorithms; bound constrained problems; large-scale problems; nonmonotone line search; projected gradients; spectral gradient method;
D O I
10.1145/502800.502803
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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.
引用
收藏
页码:340 / 349
页数:10
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