Objective acceleration and nonlinear GMRES for unconstrained optimization
This repository contains implementations of two optimization acceleration algorithms discussed in A.N. Riseth. Objective acceleration for unconstrained optimization, 2017
The code contains modifications of the original Matlab code provided by Hans De Sterck on his website.
All references to N-GMRES-O in the code correspond to the O-ACCEL algorithm in A. N. Riseth. Objective acceleration for unconstrained optimization
Requirements
These files require the Poblano toolbox for MATLAB to run.
List of relevant files
ngmres.m The N-GMRES algorithm as implemented by De Sterck
ngmres_o.m The Objective Acceleration algorithm by Riseth,
following the same structure as ngmres.o.
ngmres_test_general.m Provides convergence plots for the
different algorithms.
To show convergence plots for an instance of Problem A, with n=200, call
ngmres_test_general(0,1,200,400,true)runme_writestats.m Runs 1000 instances of each test problem and
writes the statistics to file in the directory data.
ngmres_test_tensor_CP.m Provides convergence plots for the
different algorithms on the tensor CP decomposition problem.
To show convergence plots for an instance of the problem, call
ngmres_test_tensor_CP(0,600,true)runme_writestats_tensor_CP.m Runs 1000 instances the tensor CP problem and
writes the statistics to file in the directory data.
BibTeX reference for article:
@article{riseth2017objective,
author = {Riseth, Asbj{\o}rn N.},
title = "{Objective acceleration for unconstrained optimization}",
journal = {ArXiv e-prints},
archivePrefix = "arXiv",
eprint = {1710.05200},
primaryClass = "math.OC",
keywords = {Mathematics - Optimization and Control, Mathematics - Numerical Analysis, 49M05, 65B99, 65K10},
year = 2017,
month = oct,
adsurl = {http://adsabs.harvard.edu/abs/2017arXiv171005200N},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}