Ayad Ghassane

Learning to Schedule Machines and Operators: A Human-Aware Deep Q-Learning Framework for Dynamic Flexible Job Shops

Most learning-based schedulers for job shop problems assume static workforce performance. However, dynamic dual-resource job shops must navigate stochastic disturbances and time-varying task durations due to human factors. This study proposes a human-centered Deep Reinforcement Learning framework, DD4LQN, for dynamic f...