A novel deep reinforcement learning‐based algorithm for multi‐objective energy‐efficient flow‐shop scheduling

Abstract A novel algorithm combining bidirectional recurrent neural networks (BiRNNs) with temporal difference is proposed for multi‐objective energy‐efficient non‐permutation flow‐shop scheduling problem (NFSP). The objectives of this problem involve minimising both the makespan and total energy co...

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Bibliographic Details
Main Authors: Peng Liang, Pengfei Xiao, Zeya Li, Min Luo, Chaoyong Zhang
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:IET Collaborative Intelligent Manufacturing
Subjects:
Online Access:https://doi.org/10.1049/cim2.12121
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