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Deep reinforcement learning for solving hybrid flow shop scheduling problems with limited buffers

Conghui Wang et al.

International Journal of Production Research2026https://doi.org/10.1080/00207543.2026.2615080article
AJG 3ABDC A
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https://doi.org/https://doi.org/10.1080/00207543.2026.2615080

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@article{conghui2026,
  title        = {{Deep reinforcement learning for solving hybrid flow shop scheduling problems with limited buffers}},
  author       = {Conghui Wang et al.},
  journal      = {International Journal of Production Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/00207543.2026.2615080},
}

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Deep reinforcement learning for solving hybrid flow shop scheduling problems with limited buffers

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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