An open-source RL scheduling framework extends job shop problems with transport, buffer, setup, breakdown, stochasticity, and multi-objective features; a PPO proof of concept beats SPT and MWKR heuristics on small benchmarks.
Reinforcement Learning of Dispatching Strategies for Large-Scale Industrial Scheduling,
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A Production Scheduling Framework for Reinforcement Learning Under Real-World Constraints
An open-source RL scheduling framework extends job shop problems with transport, buffer, setup, breakdown, stochasticity, and multi-objective features; a PPO proof of concept beats SPT and MWKR heuristics on small benchmarks.