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arXiv · 2605.02461

Middle-mile logistics through the lens of goal-conditioned reinforcement learning

Onno Eberhard·Thibaut Cuvelier·Michal Valko·Bruno De Backer
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Abstract

Middle-mile logistics describes the problem of routing parcels through a network of hubs linked by trucks with finite capacity. We rephrase this as a multi-object goal-conditioned MDP. Our method combines graph neural networks with model-free RL, extracting small feature graphs from the environment state.

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Onno Eberhard, Thibaut Cuvelier, Michal Valko, Bruno De Backer. 2026-05-04. Middle-mile logistics through the lens of goal-conditioned reinforcement learning. https://arxiv.org/abs/2605.02461

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