A discrete event simulator to implement deep reinforcement learning for the dynamic flexible job shop scheduling problem.
Lorenzo TiacciAndrea RossiPublished in: Simul. Model. Pract. Theory (2024)
Keyphrases
- discrete event
- simulation model
- reinforcement learning
- dynamic systems
- discrete event simulation
- hybrid systems
- crisis response
- multi objective
- discrete event systems
- dynamical systems
- function approximation
- learning algorithm
- multiple faults
- supervisory control
- manufacturing process
- dynamic environments
- model free
- job shop scheduling problem
- mathematical modeling
- markov decision processes
- low cost
- decision making
- timed petri nets
- machine learning