Spectral projected gradient methods for generalized tensor eigenvalue complementarity problem
Optimization and Control
2016-01-11 v1
Abstract
This paper looks at the tensor eigenvalue complementarity problem (TEiCP) which arises from the stability analysis of finite dimensional mechanical systems and is closely related to the optimality conditions for polynomial optimization. We investigate two monotone ascent spectral projected gradient (SPG) methods for TEiCP. We also present a shifted scaling-and-projection algorithm (SPA), which is a great improvement of the original SPA method proposed by Ling, He and Qi [Comput. Optim. Appl., DOI 10.1007/s10589-015-9767-z]. Numerical comparisons with some existed gradient methods in the literature are reported to illustrate the efficiency of the proposed methods.
Keywords
Cite
@article{arxiv.1601.01738,
title = {Spectral projected gradient methods for generalized tensor eigenvalue complementarity problem},
author = {Gaohang Yu and Yisheng Song and Yi Xu and Zefeng Yu},
journal= {arXiv preprint arXiv:1601.01738},
year = {2016}
}
Comments
arXiv admin note: text overlap with arXiv:1601.01399