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pro vyhledávání: '"González-Díaz, Julio"'
Autor:
González-Rodríguez, Brais, Gómez-Casares, Ignacio, Ghaddar, Bissan, González-Díaz, Julio, Pateiro-López, Beatriz
Over the last few years, there has been a surge in the use of learning techniques to improve the performance of optimization algorithms. In particular, the learning of branching rules in mixed integer linear programming has received a lot of attentio
Externí odkaz:
http://arxiv.org/abs/2406.03626
Autor:
de Dios, M. Fernández, González-Rueda, Ángel M., Banga, Julio R., González-Díaz, Julio, Penas, David R.
We consider the problem of parameter estimation in dynamic systems described by ordinary differential equations. A review of the existing literature emphasizes the need for deterministic global optimization methods due to the nonconvex nature of thes
Externí odkaz:
http://arxiv.org/abs/2405.01989
Autor:
Gómez-Casares, Ignacio, González-Rodríguez, Brais, González-Díaz, Julio, Rodríguez-Fernández, Pablo
Domain reduction techniques are at the core of any global optimization solver for NLP or MINLP problems. In this paper, we delve into several of these techniques and assess the impact they may have in the performance of an RLT-based algorithm for pol
Externí odkaz:
http://arxiv.org/abs/2403.02823
Autor:
González-Rodríguez, Brais, Alvite-Pazó, Raúl, Alvite-Pazó, Samuel, Ghaddar, Bissan, González-Díaz, Julio
Conic optimization has recently emerged as a powerful tool for designing tractable and guaranteed algorithms for non-convex polynomial optimization problems. On the one hand, tractability is crucial for efficiently solving large-scale problems and, o
Externí odkaz:
http://arxiv.org/abs/2208.05608
Autor:
Ghaddar, Bissan, Gómez-Casares, Ignacio, González-Díaz, Julio, González-Rodríguez, Brais, Pateiro-López, Beatriz, Rodríguez-Ballesteros, Sofía
The use of machine learning techniques to improve the performance of branch-and-bound optimization algorithms is a very active area in the context of mixed integer linear problems, but little has been done for non-linear optimization. To bridge this
Externí odkaz:
http://arxiv.org/abs/2204.10834
Akademický článek
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Publikováno v:
In Omega July 2021 102
Publikováno v:
In Nonlinear Analysis: Real World Applications October 2017 37:71-93
Akademický článek
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