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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| Ngôn ngữ: | English |
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Springer
2023
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| Truy cập trực tuyến: | https://link.springer.com/article/10.1007/s10845-023-02094-4 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8455 |
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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 |
8.8926115 |