A primal dual formulation through a proximal approach for non-convex variational optimization
Optimization and Control
2021-07-27 v5
Abstract
This article develops a primal dual formulation for a primal proximal approach suitable for a large class of non-convex models in the calculus of variations. The results are established through standard tools of functional analysis, convex analysis and duality theory and are applied to a Ginzburg-Landau type model. Finally, in the last two sections, we present concerning optimal conditions and another related duality principle for the model in question.
Keywords
Cite
@article{arxiv.2103.01855,
title = {A primal dual formulation through a proximal approach for non-convex variational optimization},
author = {Fabio Silva Botelho},
journal= {arXiv preprint arXiv:2103.01855},
year = {2021}
}
Comments
29 pages, a new result added