Real-time multi-resource jointed scheduling of container terminals with uncertainties using a reinforcement learning approach
Author:
Affiliation:
1. Sun Yat-sen University,School of Intelligent Systems Engineering,Guangzhou,China
Funder
Ministry of Science and Technology
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9828005/9828007/09828161.pdf?arnumber=9828161
Reference21 articles.
1. Simulation-based optimization for discharge/loading operations at a maritime container terminal
2. The integrated optimization of container terminal scheduling with uncertain factors
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4. Yard crane scheduling problem in a container terminal considering risk caused by uncertainty
5. Learning-based logistics planning and scheduling for crowdsourced parcel delivery
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3. Digital Twin Enhanced Reinforcement Learning for Integrated Scheduling in Automated Container Terminals*;2023 IEEE 19th International Conference on Automation Science and Engineering (CASE);2023-08-26
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