Computational and Applied Math Proseminar
joint with Industrial Mathematics Colloquium

Department of Mathematics, Arizona State University

Tuesday, April 7, 1998, 3:05 PM, PSF 123

Jorge J. Moré

Mathematics and Computer Science Division Argonne National Laboratory

Preconditioning Newton's Method

Abstract We describe current research on the development of the ELSO environment for the solution of large-scale optimization problems. An important goal of this research is the ability to solve large-scale problems while only requiring that the user provide code for the evaluation of a partially separable function. The development of ELSO is important because it eliminates the need to provide the gradient and sparsity pattern; in all other approaches the user needs to provide this information. In the current environment a trust region Newton method is used to solve the optimization problem and ADIFOR/SparsLinc is used to compute derivatives. In this talk we describe the theory and implementation of the trust region Newton method in ELSO. We emphasize the central role played by the choice of an incomplete Cholesky factorization as a preconditioner (scaling matrix) for the trust region method.

For further information please contact: mittelmann@asu.edu