Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Online simulation task scheduling in cloud manufacturing with cross attention and deep reinforcement learning. |
| Συγγραφείς: |
Chen, Zhen, Zhang, Lin, Laili, Yuanjun, Wang, Xiaohan, Wang, Fei |
| Πηγή: |
Journal of Intelligent Manufacturing; Dec2025, Vol. 36 Issue 8, p5779-5800, 22p |
| Θεματικοί όροι: |
Reinforcement learning, Scheduling, Digital computer simulation, Manufacturing industries, Automated planning & scheduling |
| Περίληψη: |
Online simulation task scheduling in a private cloud manufacturing platform usually requires rapid decision-making algorithms because of the characteristics of unpredictability and diversity of tasks. However, the existing approaches face challenges in generating satisfactory scheduling schemes within a limited solving time. Therefore, this paper proposes a dynamic scheduling algorithm for online simulation task scheduling that is based on cross-attention and deep reinforcement learning (DRL). A multichannel DRL-based framework with discrete event triggering is introduced to effectively recognize online scheduling environments. An innovative multistep state feature cross-attention method is proposed to address the challenge of temporal features caused by nonsimultaneous task arrivals. A case study in the semiconductor display industry with 35 diverse scheduling scenarios was conducted to evaluate the efficacy of the proposed algorithm, which was compared with six classic state-of-the-art DRL algorithms and three commonly used priority dispatching rules. The results show that the proposed algorithm maintains superior scheduling performance across multiple scheduling scenarios and outperforms the other algorithms by an average of nearly 30% when the optimization objective is considered. [ABSTRACT FROM AUTHOR] |
|
Copyright of Journal of Intelligent Manufacturing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Βάση Δεδομένων: |
Complementary Index |