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Evolutionary Trainer-based Deep Q-Network for Dynamic Flexible Job Shop Scheduling

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ETDQN

This repository is for the paper "Evolutionary Trainer-based Deep Q-Network for Dynamic Flexible Job Shop Scheduling"

Requirements

  • Python 3.9.
  • numPy
  • Pytorch
  • networkx

Run

  • Run GA_traniner.py to perform the training process with GA.
  • Run schedulingNewJObArrival.py to perform comparative experiments in new job arrival.
  • Run schedulingMachineFault.py to perform comparative experiments in machine failure.

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Evolutionary Trainer-based Deep Q-Network for Dynamic Flexible Job Shop Scheduling

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