Deep Reinforcement Learning-Enhanced Multi-Stage Stochastic Programming for Real-Time Decision-Making in Centralized Seed Packaging Systems

Authors

  • Yuqun Zhou University of Wisconsin-Madison

DOI:

https://doi.org/10.70393/6a69656173.323435

ARK:

https://n2t.net/ark:/40704/JIEAS.v2n6a13

Disciplines:

Artificial Intelligence Technology

Subjects:

Machine Learning

References:

5

Keywords:

Deep Reinforcement Learning, Multi-Stage Stochastic Programming, Real-Time Decision-Making, Seed Packaging Systems, Supply Chain Optimization

Abstract

The centralized seed packaging system faces significant challenges in dynamic decision-making due to stochastic demand fluctuations and operational constraints. This paper presents a novel hybrid approach integrating deep reinforcement learning (DRL) with multi-stage stochastic programming (MSP) to optimize decision-making processes. Our method leverages DRL for adaptive learning and MSP for uncertainty modeling, enabling real-time adjustments. Results from case studies demonstrate improved efficiency, reduced costs, and enhanced robustness compared to traditional approaches.

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Author Biography

Yuqun Zhou, University of Wisconsin-Madison

University of Wisconsin-Madison, USA.

References

Chen, Y., Liu, Z., & Zhang, X. (2020). Deep reinforcement learning for dynamic decision-making in energy systems. IEEE Transactions on Energy Conversion, 35(4), 1234–1245.

Kall, P., & Wallace, S. W. (1994). Stochastic Programming. Springer.

Liu, R., Wang, F., & Zhang, T. (2021). A hybrid approach combining reinforcement learning and stochastic optimization for healthcare logistics. Operations Research for Health Care, 10(2), 102–115.

Mnih, V., Kavukcuoglu, K., Silver, D., et al. (2015). Human-level control through deep reinforcement learning. Nature, 518(7540), 529–533.

Schulman, J., Wolski, F., Dhariwal, P., et al. (2017). Proximal policy optimization algorithms. arXiv preprint arXiv:1707.06347.

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Published

2024-12-01

How to Cite

[1]
Y. Zhou, “Deep Reinforcement Learning-Enhanced Multi-Stage Stochastic Programming for Real-Time Decision-Making in Centralized Seed Packaging Systems”, Journal of Industrial Engineering & Applied Science, vol. 2, no. 6, pp. 121–126, Dec. 2024.

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Articles

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