Shovel allocation and scheduling for open-pit mining using deep reinforcement learning-Reference-Cited by-同舟云学术

Shovel allocation and scheduling for open-pit mining using deep reinforcement learning

Published:2024-03 Issue:6 Volume:38 Page:442-459
ISSN:1748-0930
Container-title:International Journal of Mining, Reclamation and Environment
language:en
Short-container-title:International Journal of Mining, Reclamation and Environment

Author:

Noriega Roberto¹,Pourrahimian Yashar¹

Affiliation:

1. Mining and Rock Science Development and Innovation Lab (MRDIL), Department of Civil & Environmental Engineering, School of Mining and Petroleum Engineering, University of Alberta, Edmonton, Canada

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17480930.2024.2323325

Reference40 articles.

1. A systematic review of artificial intelligence and data-driven approaches in strategic open-pit mine planning

2. A review of machine learning applications for underground mine planning and scheduling

3. Machine learning in manufacturing and industry 4.0 applications

4. M. Panzer, B. Bender, and N. Gronau, Deep reinforcement learning in production planning and control: A systematic literature review, in Proc. 2nd Conf. Prod. Syst. Logist. CPSL 2021, D. Herberger and M. Hubner, eds., Leibniz Universitat Hannover, Hannover, 2021, pp. 535–545.

5. A review on reinforcement learning algorithms and applications in supply chain management

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1. Machine learning for open-pit mining: a systematic review;International Journal of Mining, Reclamation and Environment;2024-06-20