Transaction selection policy in tier-to-tier SBSRS by using Deep Q-Learning

This paper studies a Deep Q-Learning (DQL) method for transaction sequencing problems in an automated warehousing system, Shuttle-based Storage and Retrieval System (SBSRS), in which shuttles can move between tiers flexibly. Here, the system is referred to as tier-to-tier SBSRS (t-SBSRS), developed...

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Veröffentlicht in:	International journal of production research 2023-11, Vol.61 (21), p.7353-7366
Hauptverfasser:	Arslan, Bartu, Ekren, Banu Yetkin
Format:	Artikel
Sprache:	eng
Schlagworte:	agent-based simulation automated warehousing Cycle time deep reinforcement learning DQN Heuristic Heuristic methods Industrial applications Logistics Machine learning SBSRS Sequences Sequential scheduling Shuttles Warehousing
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