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Experiments with Conjugate Gradient Algorithms for Homotopy Curve Tracking
Author(s) -
Kashmira M. Irani,
Manohar P. Kamat,
Calvin J. Ribbens,
Homer F. Walker,
Layne T. Watson
Publication year - 1991
Publication title -
siam journal on optimization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.066
H-Index - 136
eISSN - 1095-7189
pISSN - 1052-6234
DOI - 10.1137/0801016
Subject(s) - mathematics , homotopy , algorithm , conjugate gradient method , jacobian matrix and determinant , n connected , pure mathematics
There are algorithms for finding zeros or fixed points of nonlinear systems of equations that are globally convergent for almost all starting points, i.e., with probability one. The essence of all such algorithms is the construction of an appropriate homotopy map and then tracking some smooth curve in the zero set of this homotopy map. HOMPACK is a mathematical software package implementing globally convergent homotopy algorithms with three different techniques for tracking a homotopy zero curve, and has separate routines for dense and sparse Jacobian matrices. The HOMPACK algorithms for sparse Jacobian matrices use a preconditioned conjugate gradient algorithm for the computation of the kernel of the homotopy Jacobian matrix, a required linear algebra step for homotopy curve tracking. Here variants of the conjugate gradient algorithm are implemented in the context of homotopy curve tracking and compared with Craig's preconditioned conjugate gradient method used in HOMPACK. The test problems used include actual large scale, sparse structural mechanics problems.

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