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A two-stage RNN-based deep reinforcement learning approach for solving the parallel machine scheduling problem with due dates and family setups

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Bibliographic Details
Main Authors: Funing, Li, Sebastian, Lang, Bingyuan, Hong
Format: Book
Language:English
Published: Springer 2023
Subjects:
NP-hard
PMSP
Online Access:https://link.springer.com/article/10.1007/s10845-023-02094-4
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8455
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spelling oai:localhost:PNK-84552023-05-16T03:51:22Z A two-stage RNN-based deep reinforcement learning approach for solving the parallel machine scheduling problem with due dates and family setups Funing, Li Sebastian, Lang Bingyuan, Hong NP-hard PMSP CC BY As an essential scheduling problem with several practical applications, the parallel machine scheduling problem (PMSP) with family setups constraints is difficult to solve and proven to be NP-hard. To this end, we present a deep reinforcement learning (DRL) approach to solve a PMSP considering family setups, aiming at minimizing the total tardiness. The PMSP is first modeled as a Markov decision process, where we design a novel variable-length representation of states and actions, so that the DRL agent can calculate a comprehensive priority for each job at each decision time point and then select the next job directly according to these priorities. Meanwhile, the variable-length state matrix and action vector enable the trained agent to solve instances of any scales. To handle the variable-length sequence and simultaneously ensure the calculated priority is a global priority among all jobs, we employ a rec 2023-05-16T03:51:22Z 2023-05-16T03:51:22Z 2023 Book https://link.springer.com/article/10.1007/s10845-023-02094-4 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8455 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic NP-hard
PMSP
spellingShingle NP-hard
PMSP
Funing, Li
Sebastian, Lang
Bingyuan, Hong
A two-stage RNN-based deep reinforcement learning approach for solving the parallel machine scheduling problem with due dates and family setups
description CC BY
format Book
author Funing, Li
Sebastian, Lang
Bingyuan, Hong
author_facet Funing, Li
Sebastian, Lang
Bingyuan, Hong
author_sort Funing, Li
title A two-stage RNN-based deep reinforcement learning approach for solving the parallel machine scheduling problem with due dates and family setups
title_short A two-stage RNN-based deep reinforcement learning approach for solving the parallel machine scheduling problem with due dates and family setups
title_full A two-stage RNN-based deep reinforcement learning approach for solving the parallel machine scheduling problem with due dates and family setups
title_fullStr A two-stage RNN-based deep reinforcement learning approach for solving the parallel machine scheduling problem with due dates and family setups
title_full_unstemmed A two-stage RNN-based deep reinforcement learning approach for solving the parallel machine scheduling problem with due dates and family setups
title_sort two-stage rnn-based deep reinforcement learning approach for solving the parallel machine scheduling problem with due dates and family setups
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s10845-023-02094-4
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8455
_version_ 1772331155785252864
score 8.887836

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