Intelligent scheduling of double-deck traversable cranes based on deep reinforcement learning
Author:
Affiliation:
1. Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai, People’s Republic of China
2. School of Economics & Management, Shanghai Maritime University, Shanghai, People’s Republic of China
Funder
Ministry of Industry and Information Technology of China
National Key Research and Development Program of China
Publisher
Informa UK Limited
Subject
Applied Mathematics,Industrial and Manufacturing Engineering,Management Science and Operations Research,Control and Optimization,Computer Science Applications
Link
https://www.tandfonline.com/doi/pdf/10.1080/0305215X.2022.2141236
Reference21 articles.
1. Resolution of a Job-Shop problem with transportation constraints: a master/slave approach
2. Multi-objective optimization for energy-efficient flexible job shop scheduling problem with transportation constraints
3. A hybrid estimation of distribution algorithm for distributed flexible job shop scheduling with crane transportations
4. Research on Adaptive Job Shop Scheduling Problems Based on Dueling Double DQN
5. Hasselt, Arthur Guez van Hado, and David Silver. 2015. “Deep Reinforcement Learning with Double Q-Learning.” Arxiv:1509.06461 [Cs]. http://arxiv.org/abs/1509.06461, December.
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