1 citations · 2 across the 8 of their papers we have counts for
8 papers
A note on the convergence guarantees of RLT-based algorithms for polynomial optimization
Alejandro Barros-González, Julio González-Díaz, Brais González-Rodríguez +1
This paper identifies and addresses a mathematical oversight in one of the foundational results on the Reformulation-Linearization Technique (RLT) for polynomial optimization. Corr…
Bound tightening in lifted formulations: (sub)solver-dependent impact on performance in RLT-based algorithms
Julio González-Díaz, Brais González-Rodríguez, Ignacio Gómez-Casares
In this paper we explore a relevant aspect of the interplay between two core elements of global optimization algorithms for nonconvex nonlinear programming problems. The first one…
An extension of an RLT-based solver to MINLP polynomial problems
Julio González-Díaz, Brais González-Rodríguez, Iria Rodríguez-Acevedo
In this paper we extend the core branch-and-bound algorithm of an RLT-based solver for continuous polynomial optimization, RAPOSa, to handle mixed-integer problems. We do so by a d…
Learning in Spatial Branching: Limitations of Strong Branching Imitation
Brais González-Rodríguez, Ignacio Gómez-Casares, Bissan Ghaddar +2
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 ru…
Impact of domain reduction techniques in polynomial optimization: A computational study
Ignacio Gómez-Casares, Brais González-Rodríguez, Julio González-Díaz +1
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 imp…
Degree reduction techniques for polynomial optimization problems
Brais González-Rodríguez, Joe Naoum-Sawaya
This paper presents a new approach to quadrify a polynomial programming problem, i.e. reduce the polynomial program to a quadratic program, before solving it. The proposed approach…
Polynomial Optimization: Enhancing RLT relaxations with Conic Constraints
Brais González-Rodríguez, Raúl Alvite-Pazó, Samuel Alvite-Pazó +2
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, tract…
Learning for Spatial Branching: An Algorithm Selection Approach
Bissan Ghaddar, Ignacio Gómez-Casares, Julio González-Díaz +3
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,…