Time-Lag-Aware Deep Reinforcement Learning for Flexible Job-Shop Scheduling in PPVC Module Factories

Deep reinforcement learning for flexible job-shop scheduling in PPVC module factories, where schedules must respect time lags between operations, machine setups, availability windows and shared transport resources. Optimality bounds are used in reward design and credit assignment.

@unpublished{zhangtimelagaware,
  title     = {Time-Lag-Aware Deep Reinforcement Learning for Flexible Job-Shop Scheduling in PPVC Module Factories},
  author    = {Zhang, Z. and Zhang, W.},
  note      = {Under review at IEEE Transactions on Industrial Informatics}
}

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