Optimizing Job Shop Scheduling in the Furniture Industry: A Reinforcement Learning Approach Considering Machine Setup, Batch Variability, and Intralogistics
Fuente:
arXiv
Saved in:
| Main Authors: | Schneevogt, Malte, Binninger, Karsten, Klarmann, Noah |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
An Analysis of the Coordination Gap between Joint and Modular Learning for Job Shop Scheduling with Transportation Resources
by: Link, Moritz, et al.
Published: (2026)
by: Link, Moritz, et al.
Published: (2026)
Deep Reinforcement Learning for Flexible Job Shop Scheduling with Random Job Arrivals
by: Tang, Yu, et al.
Published: (2026)
by: Tang, Yu, et al.
Published: (2026)
Iterative Learning Control-Informed Reinforcement Learning for Batch Process Control
by: Lin, Runze, et al.
Published: (2026)
by: Lin, Runze, et al.
Published: (2026)
ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule
by: Huang, Yilie, et al.
Published: (2026)
by: Huang, Yilie, et al.
Published: (2026)
Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job-Shop Scheduling
by: Li, Sirui, et al.
Published: (2025)
by: Li, Sirui, et al.
Published: (2025)
Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems
by: Smit, Igor G., et al.
Published: (2024)
by: Smit, Igor G., et al.
Published: (2024)
Learning-enabled Flexible Job-shop Scheduling for Scalable Smart Manufacturing
by: Moon, Sihoon, et al.
Published: (2024)
by: Moon, Sihoon, et al.
Published: (2024)
A Production Scheduling Framework for Reinforcement Learning Under Real-World Constraints
by: Hoss, Jonathan, et al.
Published: (2025)
by: Hoss, Jonathan, et al.
Published: (2025)
Investigating the Monte-Carlo Tree Search Approach for the Job Shop Scheduling Problem
by: Boveroux, Laurie, et al.
Published: (2025)
by: Boveroux, Laurie, et al.
Published: (2025)
Improving Mixed-Criticality Scheduling with Reinforcement Learning
by: El-Mahdy, Muhammad, et al.
Published: (2025)
by: El-Mahdy, Muhammad, et al.
Published: (2025)
Cost Optimized Scheduling in Modular Electrolysis Plants
by: Henkel, Vincent, et al.
Published: (2024)
by: Henkel, Vincent, et al.
Published: (2024)
The Pump Scheduling Problem: A Real-World Scenario for Reinforcement Learning
by: Donâncio, Henrique, et al.
Published: (2022)
by: Donâncio, Henrique, et al.
Published: (2022)
Unified Crew Planning and Replanning Optimization in Multi-Line Metro Systems Considering Workforce Heterogeneity
by: Chen, Qihang
Published: (2025)
by: Chen, Qihang
Published: (2025)
Bridging the Sim-to-Real Gap in Reinforcement Learning-Based Industrial Dispatching through Execution Semantics
by: Hoss, Jonathan, et al.
Published: (2026)
by: Hoss, Jonathan, et al.
Published: (2026)
DiAReL: Reinforcement Learning with Disturbance Awareness for Robust Sim2Real Policy Transfer in Robot Control
by: Malmir, Mohammadhossein, et al.
Published: (2023)
by: Malmir, Mohammadhossein, et al.
Published: (2023)
QoS-Aware Scheduling in New Radio Using Deep Reinforcement Learning
by: Stigenberg, Jakob, et al.
Published: (2021)
by: Stigenberg, Jakob, et al.
Published: (2021)
Optimizing Traffic Signal Control using High-Dimensional State Representation and Efficient Deep Reinforcement Learning
by: Francis, Lawrence, et al.
Published: (2024)
by: Francis, Lawrence, et al.
Published: (2024)
A New Paradigm in Tuning Learned Indexes: A Reinforcement Learning Enhanced Approach
by: Wang, Taiyi, et al.
Published: (2025)
by: Wang, Taiyi, et al.
Published: (2025)
Attention-based Reinforcement Learning for Combinatorial Optimization: Application to Job Shop Scheduling Problem
by: Lee, Jaejin, et al.
Published: (2024)
by: Lee, Jaejin, et al.
Published: (2024)
Variational Approach for Job Shop Scheduling
by: Oh, Seung Heon, et al.
Published: (2026)
by: Oh, Seung Heon, et al.
Published: (2026)
Deep Reinforcement Learning Optimization for Uncertain Nonlinear Systems via Event-Triggered Robust Adaptive Dynamic Programming
by: Bai, Ningwei, et al.
Published: (2025)
by: Bai, Ningwei, et al.
Published: (2025)
Control-Optimized Deep Reinforcement Learning for Artificially Intelligent Autonomous Systems
by: Fivel, Oren, et al.
Published: (2025)
by: Fivel, Oren, et al.
Published: (2025)
Deep Reinforcement Learning for Wireless Scheduling in Distributed Networked Control
by: Pang, Gaoyang, et al.
Published: (2021)
by: Pang, Gaoyang, et al.
Published: (2021)
A Hierarchical Signal Coordination and Control System Using a Hybrid Model-based and Reinforcement Learning Approach
by: Peng, Xianyue, et al.
Published: (2025)
by: Peng, Xianyue, et al.
Published: (2025)
Parallel Batch Scheduling With Incompatible Job Families Via Constraint Programming
by: Huertas, Jorge A., et al.
Published: (2024)
by: Huertas, Jorge A., et al.
Published: (2024)
Offline Reinforcement Learning for Learning to Dispatch for Job Shop Scheduling
by: van Remmerden, Jesse, et al.
Published: (2024)
by: van Remmerden, Jesse, et al.
Published: (2024)
Deep Reinforcement Learning for Multi-Objective Optimization: Enhancing Wind Turbine Energy Generation while Mitigating Noise Emissions
by: de Frutos, Martín, et al.
Published: (2024)
by: de Frutos, Martín, et al.
Published: (2024)
Perimeter Control with Heterogeneous Metering Rates for Cordon Signals: A Physics-Regularized Multi-Agent Reinforcement Learning Approach
by: Yu, Jiajie, et al.
Published: (2023)
by: Yu, Jiajie, et al.
Published: (2023)
Near-Real-Time Resource Slicing for QoS Optimization in 5G O-RAN using Deep Reinforcement Learning
by: Yan, Peihao, et al.
Published: (2025)
by: Yan, Peihao, et al.
Published: (2025)
Semantic-aware Transmission Scheduling: a Monotonicity-driven Deep Reinforcement Learning Approach
by: Chen, Jiazheng, et al.
Published: (2023)
by: Chen, Jiazheng, et al.
Published: (2023)
A Systems Theoretic Approach to Online Machine Learning
by: Preez, Anli du, et al.
Published: (2024)
by: Preez, Anli du, et al.
Published: (2024)
Game-Theoretic Modeling of Vehicle Unprotected Left Turns Considering Drivers' Bounded Rationality
by: Lian, Yuansheng, et al.
Published: (2025)
by: Lian, Yuansheng, et al.
Published: (2025)
Scalable Production Scheduling: Linear Complexity via Unified Homogeneous Graphs
by: Hoss, Jonathan, et al.
Published: (2026)
by: Hoss, Jonathan, et al.
Published: (2026)
Offline Reinforcement Learning for Microgrid Voltage Regulation
by: Yang, Shan, et al.
Published: (2025)
by: Yang, Shan, et al.
Published: (2025)
Why Reinforcement Learning in Energy Systems Needs Explanations
by: Butt, Hallah Shahid, et al.
Published: (2024)
by: Butt, Hallah Shahid, et al.
Published: (2024)
Data Center Cooling System Optimization Using Offline Reinforcement Learning
by: Zhan, Xianyuan, et al.
Published: (2025)
by: Zhan, Xianyuan, et al.
Published: (2025)
Addressing Terminal Constraints in Data-Driven Demand Response Scheduling
by: Bloor, Maximilian, et al.
Published: (2026)
by: Bloor, Maximilian, et al.
Published: (2026)
Optimized Task Assignment and Predictive Maintenance for Industrial Machines using Markov Decision Process
by: Nasir, Ali, et al.
Published: (2024)
by: Nasir, Ali, et al.
Published: (2024)
Safety Optimized Reinforcement Learning via Multi-Objective Policy Optimization
by: Honari, Homayoun, et al.
Published: (2024)
by: Honari, Homayoun, et al.
Published: (2024)
Survey and Tutorial of Reinforcement Learning Methods in Process Systems Engineering
by: Bloor, Maximilian, et al.
Published: (2025)
by: Bloor, Maximilian, et al.
Published: (2025)
Similar Items
-
An Analysis of the Coordination Gap between Joint and Modular Learning for Job Shop Scheduling with Transportation Resources
by: Link, Moritz, et al.
Published: (2026) -
Deep Reinforcement Learning for Flexible Job Shop Scheduling with Random Job Arrivals
by: Tang, Yu, et al.
Published: (2026) -
Iterative Learning Control-Informed Reinforcement Learning for Batch Process Control
by: Lin, Runze, et al.
Published: (2026) -
ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule
by: Huang, Yilie, et al.
Published: (2026) -
Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job-Shop Scheduling
by: Li, Sirui, et al.
Published: (2025)