Título inglés |
On diagonally preconditioning the 2-steps BFGS method with accumulated steps for supra-scale linearly constrained nonlinear programming. |
Título español |
Precondicionamiento diagonal del método BFGS de 2 etapas con etapas acumuladas para programación no lineal restringida linealmente en supraescala. |
Autor/es |
Escudero, Laureano F. |
Organización |
Cent. Invest. UAM-IBM, Madrid, España |
Revista |
0210-8054 |
Publicación |
1982, 6 (4): 333-349, 24 Ref. |
Tipo de documento |
articulo |
Idioma |
Inglés |
Resumen inglés |
We present an algorithm for supra-scale linearly constrained nonlinear programming (LNCP) based on the Limited-Storage Quasi-Newton's method. In large-scale programming solving the reduced Newton equation at each iteration can be expensive and may not be justified when far from a local solution; besides, the amount of storage required by the reduced Hessian matrix, and even the computing time for its Quasi-Newton approximation, may be prohibitive. An alternative based on the reduced Truncated-Newton methodology, that has been proved to be satisfactory for super-scale problems, is not recommended for supra-scale problems since it requires an additional gradient evaluation and the solving of two systems of linear equations per each minor iteration. It is recommended a 2-steps BFGS approximation of the inverse of the reduced Hessian matrix such that it does not require to store any matrix since the product matrix-vector is the vector to be approximated; it uses the reduced gradient and solution related to the two previous iterations and the so-termed restart iteration. A diagonal direct BFGS preconditioning is used. |
Clasificación UNESCO |
120711 |
Palabras clave español |
Algoritmos ; Programación no lineal ; Método de Newton |
Acceso al artículo completo |