1 citations · 1 across the 4 of their papers we have counts for
4 papers
Improving Cross-Problem Vehicle Routing with Locally Augmented Preferences and Representation Disentanglement
Arthur Corrêa, Paulo Nascimento, Samuel Moniz
Multi-task vehicle routing problem (VRP) solvers seek to handle multiple VRP variants within a single unified model, avoiding the need to train a separate model for every variant.…
FiLMMeD: Feature-wise Linear Modulation for Cross-Problem Multi-Depot Vehicle Routing
Arthur Corrêa, Paulo Nascimento, Samuel Moniz
Solving practical multi-depot vehicle routing problems (MDVRP) is a challenging optimization task central to modern logistics, increasingly driven by e-commerce. To address the MDV…
Unraveling the Rainbow: can value-based methods schedule?
Arthur Corrêa, Alexandre Jesus, Paulo Nascimento +2
In this work, we conduct an extensive empirical study of several deep reinforcement learning algorithms on two challenging combinatorial optimization problems: the job-shop and fle…
TuneNSearch: a hybrid transfer learning and local search approach for solving vehicle routing problems
Arthur Corrêa, Cristóvão Silva, Liming Xu +2
This paper introduces TuneNSearch, a hybrid transfer learning and local search approach for addressing diverse variants of the vehicle routing problem (VRP). Our method uses reinfo…