Computing a search direction for large scale linearly constrained nonlinear optimization calculations
Mario Arioli, Tony Fan-Cheong Chan, Iain Duff, Nicholas I. M. Gould, John K. Reid · 1993
. We consider the computation of Newton-like search directions that are appropriate when solving large-scale linearly-constrained nonlinear optimization problems. We investigate the use of both direct and iterative methods and consider efficient ways of modifying the Newton equations in order to ensure global convergence of the underlying optimization methods. 1 Parallel Algorithms Team, CERFACS, 42 Ave. G. Coriolis, 31057 Toulouse Cedex, France 2 IAN-CNR, c/o Dipartimento di Matematica, 209, via Abbiategrasso 27100 Pavia, Italy 3 Department of Mathematics, University of California, 405 Hilgard Avenue, Los Angeles, CA 90024-1555, USA 4 Central Computing Department, Rutherford Appleton Laboratory, Chilton, Oxfordshire, OX11 0QX, England 5 Current reports available by anonymous ftp from the directory "pub/reports" on camelot.cc.rl.ac.uk (internet 130.246.8.61) Keywords: Large-scale problems, unconstrained optimization, linearly constrained optimization, direct methods, iterative...