NAME
TOMS768 or TENSOLVE
PURPOSE
Solving systems of nonlinear equations.
REFERENCE
Bouaricha, Ali, and Schnabel, Robert B. (1997). Algorithm 768. TENSOLVE: A software package for solving systems of nonlinear equations and nonlinear least-squares problems using tensor methods. ACM Transactions on Mathematical Software, 23(2), 174-195.
ABSTRACT OR SUMMARY
This article describes a modular software package for solving systems of nonlinear equations and nonlinear problems, using a new class of methods called tensor methods. It is intended for small- to medium-sized problems, say with up to 100 equations and unknowns, in cases where it is reasonable to calculate the Jacobian matrix or to approximate it by finite differences at each iteration. The software allows the user to choose between a tensor method and a standard method based on a linear model. The tensor method approximates F(x) by a quadratic model, where the second-order term is chosen so that the model is hardly more expensive to form, store, or solve than the standard linear model. Moreover, the software provides two different global strategies: a line search approach and a two-dimensional trust region approach. Test results indicate that, in general, tensor methods are significantly more efficient and robust than standard methods on small- and medium-sized problems in iterations and function evaluations. [Bouaricha and Schnabel, 1997, p. 174.]
LANGUAGE
Fortran 77
LICENSE
All software, both binary and source published by the Association for Computing Machinery (hereafter, Software) is copyrighted by the Association (hereafter, ACM) and ownership of all right, title and interest in and to the Software remains with ACM. By using or copying the Software, User agrees to abide by the terms of this Agreement. The URL for the ACM Software Copyright and License Agreement is http://www.acm.org/pubs/copyright_policy/softwareCRnotice.html.
ORIGINAL CODE LOCATION
http://www.netlib.org/toms/768
ftp://ftp.cs.colorado.edu/pub/cs/distribs/tensor/
TECHNICAL NOTES
None
DOWNLOAD
None