5 papers
Rethinking Positional Encoding for Neural Vehicle Routing
Chuanbo Hua, Federico Berto, Andre Hottung +8
Transformer-based models have become the dominant paradigm for neural combinatorial optimization (NCO) of vehicle routing problems (VRPs), yet the role of positional encoding (PE)…
VRPAgent: LLM-Driven Discovery of Heuristic Operators for Vehicle Routing Problems
André Hottung, Federico Berto, Chuanbo Hua +9
Designing high-performing heuristics for vehicle routing problems (VRPs) is a complex task that requires both intuition and deep domain knowledge. Large language model (LLM)-based…
Neural Deconstruction Search for Vehicle Routing Problems
André Hottung, Paula Wong-Chung, Kevin Tierney
Autoregressive construction approaches generate solutions to vehicle routing problems in a step-by-step fashion, leading to high-quality solutions that are nearing the performance…
PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization
André Hottung, Mridul Mahajan, Kevin Tierney
Reinforcement learning-based methods for constructing solutions to combinatorial optimization problems are rapidly approaching the performance of human-designed algorithms. To furt…
RouteFinder: Towards Foundation Models for Vehicle Routing Problems
Federico Berto, Chuanbo Hua, Nayeli Gast Zepeda +6
This paper introduces RouteFinder, a comprehensive foundation model framework to tackle different Vehicle Routing Problem (VRP) variants. Our core idea is that a foundation model f…