Deep Reinforcement Learning for Minimizing Tardiness in Parallel Machine Scheduling With Sequence Dependent Family Setups

Deep Reinforcement Learning for Minimizing Tardiness in Parallel Machine Scheduling With Sequence Dependent Family Setups

Parallel machine scheduling with sequence-dependent family setups has attracted much attention from academia and industry due to its practical applications. In a real-world manufacturing system, however, solving the scheduling problem becomes challenging since it is required to address urgent and fr...

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Bibliographic Details
Main Authors: Bohyung Paeng, In-Beom Park, Jonghun Park
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Deep reinforcement learning
unrelated parallel machine scheduling
sequence-dependent family setups
total tardiness objective
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Online Access:https://ieeexplore.ieee.org/document/9486959/

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https://ieeexplore.ieee.org/document/9486959/

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