We show that Lasserre measure-based hierarchies for polynomial optimization can be implemented by directly computing the discrete minimum at a suitable set of algebraic quadrature nodes. The sampling cardinality can be much lower than in other approaches based on grids or norming meshes. All the vast literature on multivariate algebraic quadrature becomes in such a way relevant to polynomial optimization

Quadrature-based polynomial optimization

Martinez, Angeles;
2019-01-01

Abstract

We show that Lasserre measure-based hierarchies for polynomial optimization can be implemented by directly computing the discrete minimum at a suitable set of algebraic quadrature nodes. The sampling cardinality can be much lower than in other approaches based on grids or norming meshes. All the vast literature on multivariate algebraic quadrature becomes in such a way relevant to polynomial optimization
2019
7-mar-2019
Pubblicato
https://link.springer.com/article/10.1007/s11590-019-01416-x
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2955061
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