11 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)…
EvoNav: Evolutionary Reward Function Design for Robot Navigation with Large Language Models
Zhikai Zhao, Chuanbo Hua, Federico Berto +4
Robot navigation is a crucial task with applications to social robots in dynamic human environments. While Reinforcement Learning (RL) has shown great promise for this problem, the…
JudgeFlow: Agentic Workflow Optimization via Block Judge
Zihan Ma, Zhikai Zhao, Chuanbo Hua +2
Optimizing LLM-based agentic workflows is challenging for scaling AI capabilities. Current methods rely on coarse, end-to-end evaluation signals and lack fine-grained signals on wh…
Priority-Aware Multi-Robot Coverage Path Planning
Kanghoon Lee, Hyeonjun Kim, Jiachen Li +1
Multi-robot systems are widely used for coverage tasks that require efficient coordination across large environments. In Multi-Robot Coverage Path Planning (MCPP), the objective is…
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…
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…