Barzilai and Borwein conjugate gradient method equipped with a non-monotone line search technique and its application on non-negative matrix factorization
Optimization and Control
2022-11-15 v1 Machine Learning
Abstract
In this paper, we propose a new non-monotone conjugate gradient method for solving unconstrained nonlinear optimization problems. We first modify the non-monotone line search method by introducing a new trigonometric function to calculate the non-monotone parameter, which plays an essential role in the algorithm's efficiency. Then, we apply a convex combination of the Barzilai-Borwein method for calculating the value of step size in each iteration. Under some suitable assumptions, we prove that the new algorithm has the global convergence property. The efficiency and effectiveness of the proposed method are determined in practice by applying the algorithm to some standard test problems and non-negative matrix factorization problems.
Keywords
Cite
@article{arxiv.2109.05685,
title = {Barzilai and Borwein conjugate gradient method equipped with a non-monotone line search technique and its application on non-negative matrix factorization},
author = {Sajad Fathi Hafshejani and Daya Gaur and Shahadat Hossain and Robert Benkoczi},
journal= {arXiv preprint arXiv:2109.05685},
year = {2022}
}