A novel carbon reduction engineering method-based deep Q-learning algorithm for energy-efficient scheduling on a single batch-processing machine in semiconductor manufacturing

Min Konga School of Economics and Management, Anhui Normal University, Wuhu, People’s Republic of China;b School of Management, Hefei University of Technology, Hefei, People’s Republic of ChinaView further author information

Weizhong Wanga School of Economics and Management, Anhui Normal University, Wuhu, People’s Republic of ChinaView further author information

Muhammet Devecic The Bartlett School of Sustainable Construction, University College London, London, UK;d Department of Industrial Engineering, Turkish Naval Academy, National Defence University, Tuzla, Istanbul, TurkeyCorrespondence[email protected]
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Yajing Zhanga School of Economics and Management, Anhui Normal University, Wuhu, People’s Republic of ChinaView further author information

Xuzhong Wua School of Economics and Management, Anhui Normal University, Wuhu, People’s Republic of ChinaCorrespondence[email protected]
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D'Maris Coffmanc The Bartlett School of Sustainable Construction, University College London, London, UKView further author information

A novel carbon reduction engineering method-based deep Q-learning algorithm for energy-efficient scheduling on a single batch-processing machine in semiconductor manufacturing

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A novel carbon reduction engineering method-based deep Q-learning algorithm for energy-efficient scheduling on a single batch-processing machine in semiconductor manufacturing

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