Un Método de Optimización Proximal para Problemas de Localización Cuasi-convexa
The localization problem is of great interest to establish the optimal location of the different demands in the state or private sector. The model of this problem is generally reduced to solve a mathematical optimization problem. In the present work we present a proximal optimization method to solve...
| Autor: | |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | Perú |
| Institución: | Centro de Preparación para la Ciencia y Tecnología |
| Repositorio: | ECIPERÚ |
| Idioma: | español |
| OAI Identifier: | oai:revistas.eciperu.net:article/210 |
| Acceso en línea: | https://revistas.eciperu.net/index.php/ECIPERU/article/view/210 |
| Access Level: | acceso abierto |
| Palabra clave: | Método del punto proximal, teoría de localización, convergencia global, función cuasi-convexa. Proximal point method, localization theory, global convergence, quasiconvex function. |
| Sumario: | The localization problem is of great interest to establish the optimal location of the different demands in the state or private sector. The model of this problem is generally reduced to solve a mathematical optimization problem. In the present work we present a proximal optimization method to solve localization problems where the objective function is non differentiable and quasiconvex. We prove that the iterations of the method are well defined and under some assumption on the objective function we prove the convergence of the method. |
|---|