CEA-FJSP: Carbon emission-aware flexible job-shop scheduling based on deep reinforcement learning

CEA-FJSP: Carbon emission-aware flexible job-shop scheduling based on deep reinforcement learning

Currently, excessive carbon emission is causing visible damage to the ecosystem and will lead to long-term environmental degradation in the future. The manufacturing industry is one of the main contributors to the carbon emission problem. Therefore, the reduction of carbon emissions should be consid...

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Bibliographic Details
Main Authors:	Shiyong Wang, Jiaxian Li, Hao Tang, Juan Wang
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2022-11-01
Series:	Frontiers in Environmental Science
Subjects:	smart manufacturing production scheduling deep reinforcement learning carbon emission multi-objective optimization
Online Access:	https://www.frontiersin.org/articles/10.3389/fenvs.2022.1059451/full

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