Curriculum Learning with GNN-based Reinforcement Learning for Job Shop Scheduling

arXiv:2609.28085 · cs.LG, cs.AI · Submitted 2026-09-23 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-09-23

Updated: 2026-09-23

Terminology

• Generalization — 23× in this paper · explained in 13 episodes
• Reinforcement Learning — 12× in this paper · explained in 4 episodes
• Actor — 4× in this paper · explained in 3 episodes
• Action Masking — 3× in this paper · explained in 1 episode
• Combinatorial Optimization — 3× in this paper · explained in 2 episodes
• Job Shop Scheduling Problem — 3× in this paper
• Deep Reinforcement Learning — 2× in this paper · explained in 2 episodes
• GNNs — 2× in this paper · explained in 2 episodes
• Proximal Policy Optimization — 2× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Graph Neural Network (GNN) — 1× in this paper · explained in 2 episodes
• Homogenization — 1× in this paper · explained in 2 episodes
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 4 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Zero-Shot Generalization — 1× in this paper · explained in 5 episodes

Sources

• Curriculum Learning in Job Shop Scheduling using Reinforcement Learning
• Learning to generalize Dispatching rules on the Job Shop Scheduling
• Relational inductive biases, deep learning, and graph networks
• Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization
• Proximal Policy Optimization Algorithms
• How Powerful are Graph Neural Networks?
• A Reinforcement Learning Environment For Job-Shop Scheduling
• Scalable Production Scheduling: Linear Complexity via Unified Homogeneous Graphs

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