Hybrid Jaya-Transformer-based Task Scheduling Algorithm for Super-agile Satellites

Authors

• Haoyu Zhao, School of Information Science and Technology, Hebei Agricultural University, Baoding 071001, China
• Guanghui Zhang, School of Information Science and Technology, Hebei Agricultural University, Baoding 071001, China
• Lanting Hao, School of Information Science and Technology, Hebei Agricultural University, Baoding 071001, China
• Meijia Guo, School of Information Science and Technology, Hebei Agricultural University, Baoding 071001, China

Abstract

Abstract: Super-agile satellite task scheduling is characterized by complex constraints and tight coupling among task transitions. To address the relatively long online solution times of traditional heuristic algorithms, this paper establishes a super-agile satellite task scheduling model that aims to maximize the task profit ratio while considering constraints on visible time windows, attitude transition time, energy, and storage capacity. A Transformer is used to learn task requirements, visible time windows, and global correlations among tasks, and a dynamic mask and a task scheduler are incorporated to generate feasible task sequences. To enhance the model's ability to learn complex task correlations and reduce the influence of manual hyperparameter tuning on algorithm performance, this paper proposes a hybrid Jaya-Transformer scheduling algorithm. Experimental results show that the hybrid Jaya-Transformer improves the average task profit ratio by 2.58-11.89 percentage points compared with Transformer. Compared with ALNS and IGA-LS, the proposed algorithm achieves optimal or near-optimal task profit ratios with an average solution time of only 0.21-0.78 s, substantially shorter than the 6.21-108.9 s required by the heuristic algorithms, demonstrating its ability to balance scheduling quality and solution efficiency.

Recommended Citation

Zhao, Haoyu; Zhang, Guanghui; Hao, Lanting; and Guo, Meijia (2026) "Hybrid Jaya-Transformer-based Task Scheduling Algorithm for Super-agile Satellites," Journal of System Simulation: Vol. 38: Iss. 10, Article 17.
DOI: 10.16182/j.issn1004731x.joss.26-0395
Available at: https://dc-china-simulation.researchcommons.org/journal/vol38/iss10/17

First Page

3052

Last Page

3067

CLC

TP391.9

Recommended Citation

Zhao Haoyu, Zhang Guanghui, Hao Lanting, et al. Hybrid Jaya-Transformer-based Task Scheduling Algorithm for Super-agile Satellites[J]. Journal of System Simulation, 2026, 38(10): 3052-3067.

Corresponding Author

Zhang Guanghui

DOI

10.16182/j.issn1004731x.joss.26-0395