Un Método de Optimización Proximal para Problemas de Localización Cuasi-convexa

Authors

  • Miguel A. Cano Lengua y Cols.

DOI:

https://doi.org/10.33017/RevECIPeru2011.0018/

Keywords:

Proximal point method, localization theory, global convergence, quasiconvex function.

Abstract

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.

Downloads

Published

2019-01-12

Issue

Section

ARTÍCULOS ORIGINALES