Unconstraint global polynomial optimization via Gradient Ideal
Algebraic Geometry
2013-03-22 v3
Abstract
In this paper, we describe a new method to compute the minimum of a real polynomial function and the ideal defining the points which minimize this polynomial function, assuming that the minimizer ideal is zero-dimensional. Our method is a generalization of Lasserre relaxation method and stops in a finite number of steps. The proposed algorithm combines Border Basis, Moment Matrices and Semidefinite Programming. In the case where the minimum is reached at a finite number of points, it provides a border basis of the minimizer ideal.
Cite
@article{arxiv.1301.5298,
title = {Unconstraint global polynomial optimization via Gradient Ideal},
author = {Marta Abril Bucero and Bernard Mourrain and Philippe Trebuchet},
journal= {arXiv preprint arXiv:1301.5298},
year = {2013}
}
Comments
arXiv admin note: text overlap with arXiv:1112.3197