SOURCE-LINKED INTELLIGENCE
Reinforcement Learning Enhanced LLM Agents for Complex Vehicle Routing Problems
Vehicle Routing Problems (VRPs) are fundamental combinatorial optimization problems with widespread applications in various scenarios. The advanced optimization solvers can effectively solve such problems. However, modeling complex VRP variants for solvers often requires substantial domain expertise, which limits the accessibility of advanced optimization technologies. In this paper, we propose Reinforcement Learning Enhanced LLMAgents(RLEA), a multi-agent framework designed to automate the modeling of complex VRPs. RLEA introduces a lightweight neural Planner trained with Soft Q-learning to e
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-01T07:56:15.000Z
First collected: 2026-09-21T06:11:57.537Z. This is not the publication date.