Reconfigurable manufacturing system scheduling: a deep reinforcement learning approach

Jiecheng Tang; Yousef Haddad; Konstantinos Salonitis

doi:10.1016/j.procir.2022.05.131

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JOURNAL ARTICLE

Reconfigurable manufacturing system scheduling: a deep reinforcement learning approach

Jiecheng Tang Yousef Haddad Konstantinos Salonitis

Year: 2022 Journal: Procedia CIRP Vol: 107 Pages: 1198-1203 Publisher: Elsevier BV

DOI: 10.1016/j.procir.2022.05.131

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Keywords:

Reinforcement learning Scheduling (production processes) Computer science Distributed computing Industrial engineering Engineering Artificial intelligence Operations management

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Topics

Flexible and Reconfigurable Manufacturing Systems

Physical Sciences → Engineering → Industrial and Manufacturing Engineering

Scheduling and Optimization Algorithms

Physical Sciences → Engineering → Industrial and Manufacturing Engineering

Digital Transformation in Industry

Physical Sciences → Engineering → Industrial and Manufacturing Engineering

Reconfigurable manufacturing system scheduling: a deep reinforcement learning approach

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