Monday, May 20
10:00 AM-12:00 PM
Saanich 1

MS4
Use of Iterative Methods in Optimization and Nonlinear Equations
(Part I of II)

Most algorithms for optimization problems and nonlinear equations require the solution of linear systems of equations. In many applications, the linear systems are very large while in others the coefficient matrix is not explicitly available. These difficulties suggest the use of iterative solvers. The goal of this minisymposium is to present new ideas concerning the use of iterative methods in several algorithmic frameworks for solving optimization problems and nonlinear equations. The presentations given here will address practical as well as theoretical issues concerning this topic. Some of these issues are the use of Krylov subspace methods, preconditioning, limited memory QuasiNewton updates, and inexactness.

Organizers: Amr S. El-Bakry, Alexandria University, Egypt; and
Luis N. Vicente, Rice University

Truncated-Newton Methods for Large-Scale Optimization
Steven G. Nash, George Mason University
Preconditioning of Elliptic Variational Inequalities
Tony Choi, North Carolina State University
Newton-Krylov Methods
Homer F. Walker, Utah State University
Computational Experiments with Iterative Solvers for Primal-Dual Interior-Point Methods in Nonlinear Programming
Amr S. El-Bakry, Organizer

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LMH, 3/15/96