Categories
M1QN3
The routine M1QN3 has been designed to minimize functions depending on a very large number of variables (several hundred million is sometimes possible) not subject to constraints. It implements a limited memory quasi-Newton technique (the L-BFGS method of J. Nocedal) with a dynamically updated scalar or diagonal preconditioner. It uses line-search to enforce global convergence; more precisely, the step-size is determined by the Fletcher-Lemaréchal algorithm and realizes the Wolfe conditions.
Last updated 14 Jan, 2009
Versions
3.2
- Released: 14 Jan, 2009
- Code Maturity: Mature
- Source Archive: http://www-rocq.inria.fr/estime/modulopt/optimi...
- Licenses: GPLv3
- Interfaces: Library
User Community and Support
http://www-rocq.inria.fr/estime/modulopt/optimization-routines/m1qn3/m1qn3-documentation.html




