A proximal method to solve quasiconvex non-differentiable location problems

Thumbnail
Date
2020-05-01
Author(s)
Cano Lengua, Miguel Angel
Papa Quiroz, Erik Alex
Metadata
Show full item record
Abstract
ABSTRACT The location problem is of great interest in order to establish different location demands in the state or private sector. The model of this problem is usually reduced to a mathematical optimization problem. In this paper we present a proximal method to solve location problems where the objective function is quasi-convex and non-differentiable. We prove that the iterations given by the method are well defined and under some assumptions on the objective function we prove the convergence of the method.
Mostrar más
URI
https://hdl.handle.net/11537/27231
Bibliographic citation
Cano, M. A., & Papa, E. A. (2020). A Proximal method to solve quasiconvex non-differentiable location problems. ICMSSP 2020: Proceedings of the 2020 5th International Conference on Multimedia Systems and Signal Processing, 98-104. https://doi.org/10.1145/3404716.3404735
Note
El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.
Subject
Collections

The following license files are associated with this item:

info:eu-repo/semantics/openAccess
Except where otherwise noted, this item's license is described as info:eu-repo/semantics/openAccess