A reinforcement learning approach for transaction scheduling in a shuttle‐based storage and retrieval system

DOI10.1111/itor.13135OpenAlexW4220881999MaRDI QIDQ6082273

Banu Yetkin Ekren, Unnamed Author

Publication date: 29 November 2023

Published in: International Transactions in Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/itor.13135

zbMATH Keywords

simulationreinforcement learningwarehousing\(Q\)-learningSBS/RSautomated storage

Mathematics Subject Classification ID

Operations research, mathematical programming (90-XX)

Cites Work

• Modeling parallel movement of lifts and vehicles in tier-captive vehicle-based warehousing systems
• Approximate analysis of load-dependent generally distributed queuing networks with low service time variability
• Machine learning for combinatorial optimization: a methodological tour d'horizon
• An open queuing network-based tool for performance estimations in a shuttle-based storage and retrieval system
• Simulation-based optimization. Parametric optimization techniques and reinforcement learning
• A tool for time, variance and energy related performance estimations in a shuttle-based storage and retrieval system
• Cost and performance comparison for tier‐captive and tier‐to‐tier SBS/RS warehouse configurations

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