A reinforcement learning framework formulated as an event-driven semi-Markov decision process with graph states and action masking outperforms heuristic and optimization baselines for stochastic electric truck routing under charging constraints.
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Learning to Route Electric Trucks Under Operational Uncertainty
A reinforcement learning framework formulated as an event-driven semi-Markov decision process with graph states and action masking outperforms heuristic and optimization baselines for stochastic electric truck routing under charging constraints.