Least-Squares#
Release: 1.0
Date: 18 June 2024
Author: Jaroslav Fowkes and Nick Gould
GALAHAD [1] is a suite of open-source routines for large-scale continuous optimization. Currently there is a single package designed to find a local minimizer of a sum-of-squares function whose variables may take any values, a second pair that target linear problems with simple bounds on the variables, another for which the feasible region is a regular simplex, and a final one for which the constraints are linear (polyhedral).
Contents
- BLLS - bound-constrained linear least-squares using a preconditioned, projected-gradient method
- BLLSB - bound-constrained linear least-squares using an interior-point method
- CLLS - linearly-constrained linear least-squares using an interior-point method
- NLS - unconstrained local nonlinear least-squares using a regularization method
- SLLS - simplex-constrained linear least-squares using a preconditioned, projected-gradient method