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.
|Title of host publication||Proceedings of the 2020 5th International Conference on Multimedia Systems and Signal Processing, ICMSSP 2020|
|Number of pages||7|
|State||Published - 28 May 2020|
|Event||5th International Conference on Multimedia Systems and Signal Processing, ICMSSP 2020 - Chengdu, China|
Duration: 28 May 2020 → 30 May 2020
|Name||PervasiveHealth: Pervasive Computing Technologies for Healthcare|
|Conference||5th International Conference on Multimedia Systems and Signal Processing, ICMSSP 2020|
|Period||28/05/20 → 30/05/20|
Bibliographical notePublisher Copyright:
© 2020 ACM.
- Global convergence
- Location theory
- Proximal point method
- Quasiconvex function