Deep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions

Machine scheduling aims to optimally assign jobs to a single or a group of machines while meeting manufacturing rules as well as job specifications. Optimizing the machine schedules leads to significant reduction in operational costs, adherence to customer demand, and rise in production efficiency....

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Veröffentlicht in:	Computers & industrial engineering Jg. 200; S. 110856
Hauptverfasser:	Khadivi, Maziyar, Charter, Todd, Yaghoubi, Marjan, Jalayer, Masoud, Ahang, Maryam, Shojaeinasab, Ardeshir, Najjaran, Homayoun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.02.2025
Schlagworte:	Artificial intelligence Deep reinforcement learning Graph neural networks Machine scheduling Neural combinatorial optimization Production scheduling Neural combinatorial optimization Deep reinforcement learning Machine scheduling Graph neural networks Production scheduling Artificial intelligence
ISSN:	0360-8352
Online-Zugang:	Volltext
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