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.
Original language | English |
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Title of host publication | Proceedings of the 2020 5th International Conference on Multimedia Systems and Signal Processing, ICMSSP 2020 |
Publisher | Association for Computing Machinery |
Pages | 98-104 |
Number of pages | 7 |
ISBN (Electronic) | 9781450377485 |
DOIs | |
State | Published - 28 May 2020 |
Externally published | Yes |
Event | 5th International Conference on Multimedia Systems and Signal Processing, ICMSSP 2020 - Chengdu, China Duration: 28 May 2020 → 30 May 2020 |
Publication series
Name | ACM International Conference Proceeding Series |
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Conference
Conference | 5th International Conference on Multimedia Systems and Signal Processing, ICMSSP 2020 |
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Country/Territory | China |
City | Chengdu |
Period | 28/05/20 → 30/05/20 |
Bibliographical note
Publisher Copyright:© 2020 ACM.
Keywords
- Global convergence
- Location theory
- Proximal point method
- Quasiconvex function