12 citations · 21 across the 4 of their papers we have counts for
5 papers
A First Guess Is Rarely the Final Answer: Learned Local Search That Generalizes to Larger Routing Problems
Andoni Irazusta Garmendia
Neural routing solvers rarely stop at their first solution: constructed tours are usually refined by search, such as sampling or local search. Neural improvement methods learn this…
Enabling Population-Based Architectures for Neural Combinatorial Optimization
Andoni Irazusta Garmendia, Josu Ceberio, Alexander Mendiburu
Neural Combinatorial Optimization (NCO) has mostly focused on learning policies, typically neural networks, that operate on a single candidate solution at a time, either by constru…
MARCO: A Memory-Augmented Reinforcement Framework for Combinatorial Optimization
Andoni I. Garmendia, Quentin Cappart, Josu Ceberio +1
Neural Combinatorial Optimization (NCO) is an emerging domain where deep learning techniques are employed to address combinatorial optimization problems as a standalone solver. Des…
Neural Improvement Heuristics for Graph Combinatorial Optimization Problems
Andoni I. Garmendia, Josu Ceberio, Alexander Mendiburu
Recent advances in graph neural network architectures and increased computation power have revolutionized the field of combinatorial optimization (CO). Among the proposed models fo…
Neural Combinatorial Optimization: a New Player in the Field
Andoni I. Garmendia, Josu Ceberio, Alexander Mendiburu
Neural Combinatorial Optimization attempts to learn good heuristics for solving a set of problems using Neural Network models and Reinforcement Learning. Recently, its good perform…