Optimizing satellite ground station facilities scheduling for RSGS: a novel model and algorithm

References

• An, Y., W. Li, W. Wang, X. Yang, P. Wei, and X. Wang. 2021. “Research on Schedule Strategy of Ground Stations for LEO Satellites.” Journal of Time and Frequency 44 (2): 120–131.
   Google Scholar
• Falone, R., and G. Corrao. 2018. “Ground Station Network Scheduling Through Genetic and Deterministic Combined Algorithm.” Paper Presented at the 2018 Space Ops Conference, Palais du Pharo, May 28–June 1.
   Google Scholar
• Fan, H., W. Zhang, M. Tian, G. Ma, and B. Cheng. 2022. “A Resource Scheduling Method for Satellite Mission Ground Station Based on Particle Swarm Optimization Algorithm.” Journal of University of Chinese Academy of Sciences 39 (6): 801–808. https://doi.org/10.7523/j.ucas.2021.0012.
   Google Scholar
• Goldberg, D. E. 1989. Genetic Algorithms in Search, Optimization, and Machine Learning. Boston, MA: Addison-Wesley.
   Google Scholar
• Harjunkoski, I., C. T. Maravelias, P. Bongers, P. M. Castro, S. Engell, I. E. Grossmann, J. Hooker, C. Mendez, G. Sand, and J. Wassick. 2014. “Scope for Industrial Applications of Production Scheduling Models and Solution Methods.” Computers & Chemical Engineering 62:161–193. https://doi.org/10.1016/j.compchemeng.2013.12.001.
   Web of Science ®Google Scholar
• Iacopino, C., P. Palmer, N. Policella, and A. Donati. 2014. “Planning the GENSO Ground Station Network via an Ant Colony-Based Approach.” Paper Presented at the 13th International Conference on Space Operations, Pasadena, CA, May 2014. https://doi.org/10.2514/6.2014-1704.
   Google Scholar
• Kennedy, J. 2005. “Why Does It Need Velocity?” Paper Presented at Proceedings of the IEEE Swarm Intelligence Symposium (SIS’05), Pasadena, CA, June 8–10.
   Google Scholar
• Kennedy, J., and R. Eberhart. 1995. “Particle Swarm Optimization.” Paper Presented at Proceedings of the IEEE International Conference on Neural Networks, Perth, November 27–December 1. https://doi.org/10.1109/ICNN.1995.487241.
   Google Scholar
• Ko, H. P. 2016. “Discretized Genetic Algorithm for Satellite Constellation and Multiple Ground Antenna Scheduling.” Paper Presented at the 14th International Conference on Space Operations, Daejeon, May 16–20.
   Google Scholar
• Li, X., X. Guo, H. Tang, R. Wu, and J. Liu. 2023. “An Improved Cuckoo Search Algorithm for the Hybrid Flow-Shop Scheduling Problem in Sand Casting Enterprises Considering Batch Processing.” Computers & Industrial Engineering 176. https://doi.org/10.1016/j.cie.2022.108921.
   Web of Science ®Google Scholar
• Li, Y., R. Wang, Y. Liu, and M. Xu. 2015. “Satellite Range Scheduling with the Priority Constraint: An Improved Genetic Algorithm Using a Station ID Encoding Method.” Chinese Journal of Aeronautics 28 (3): 789–803. https://doi.org/10.1016/j.cja.2015.04.012 .
   Web of Science ®Google Scholar
• Li, J., T. Zhang, and G. Ye. 2015. “Satellite-Ground TT&C United Scheduling Methods of GNSS Constellation Based on Nodes Constraint.” In Vol.1 of China Satellite Navigation Conference (CSNC) 2015 Proceedings, 55–66. Heidelberg: Springer .
   Google Scholar
• Lin, W. C., C. Y. Liu, D. Y. Liao, and Y. Y. Lee. 2003. “Daily Imaging Scheduling of an Earth Observation Satellite.” Poster Presented at the 2003 IEEE International Conference on Systems, Man and Cybernetics. Washington, DC, October 5–8.
   Google Scholar
• Marinelli, F., S. Nocella, F. Rossi, and S. Smriglio. 2011. “A Lagrangian Heuristic for Satellite Range Scheduling with Resource Constraints.” Computers & Operations Research 38 (11): 1572–1583. https://doi.org/10.1016/j.cor.2011.01.016.
   Web of Science ®Google Scholar
• Petelin, G., M. Antoniou, and G. Papa. 2021. “Multi-Objective Approaches to Ground Station Scheduling for Optimization of Communication with Satellites.” Optimization and Engineering. https://doi.org/10.1007/s11081-021-09617-z.
   Web of Science ®Google Scholar
• Shang, X., Y. Feng, J. Chen, W. Zhang, P. Huang, Q. Kong, L. Han, et al. 2014. Ground receiving resource allocation method based on receiving resource capability constraints. China Patent CN201410310281.0, filed October, 22.
   Google Scholar
• Song, Y., B. Song, L. Xing, Y. Jia, and Y. Chen. 2022. “Improved Artificial Bee Colony Algorithm for Satellite-Ground Cooperative Observation Planning Problem.” Control and Decision 37 (3): 555–564. https://doi.org/10.13195/j.kzyjc.2020.1459.
   Google Scholar
• Spangelo, S., J. Cutler, K. Gilson, and A. Cohn. 2015. “Optimization-Based Scheduling for the Single-Satellite, Multi-Ground Station Communication Problem.” Computers & Operations Research 57:1–16. https://doi.org/10.1016/j.cor.2014.11.004.
   Web of Science ®Google Scholar
• Sun, J., and F. Xhafa. 2011. “A Genetic Algorithm for Ground Station Scheduling.” Paper Presented at International Conference on Complex, Intelligent and Software Intensive Systems, Seoul, June 30–July 2.
   Google Scholar
• Tian, M., S. Xu, P. Huang, G. Ma, and K. Feng. 2020. “Intelligent Scheduling Method for Satellite Ground Station Resources.” In Proceedings of the 39th Chinese Control Conference, 392–397. Shenyang: IEEE.
   Google Scholar
• Wang, Z., Z. Zhang, and Y. Chen. 2019. “Multi-Objective Optimization of Satellite-Ground Time Synchronization Scheduling Problem.” In Proceedings of the 2019 IEEE Congress on Evolutionary Computation (CEC), 530–537. Wellington: IEEE.
   Google Scholar
• Xhafa, F., and W. H. Andrew. 2021. “Optimisation Problems and Resolution Methods in Satellite Scheduling and Space-Craft Operation: A Survey.” Enterprise Information Systems 15 (8): 1022–1045. https://doi.org/10.1080/17517575.2019.1593508.
   Google Scholar
• Xhafa, F., A. Barolli, and M. Takizawa. 2013. “Steady State Genetic Algorithm for Ground Station Scheduling Problem.” Paper Presented at 2013 IEEE 27th International Conference on Advanced Information Networking and Applications, Barcelona, March 25–28 .
   Google Scholar
• Xhafa, F., X. Herrero, A. Barolli, L. Barolli, and M. Takizawa. 2013. “Evaluation of Struggle Strategy in Genetic Algorithms for Ground Stations Scheduling Problem.” Journal of Computer and System Sciences 79 (7): 1086–1100. https://doi.org/10.1016/J.JCSS.2013.01.023 .
   Web of Science ®Google Scholar
• Xhafa, F., J. Sun, A. Barolli, M. Takizawa, and K. Uchida. 2012. “Evaluation of Genetic Algorithms for Single Ground Station Scheduling Problem.” In 2012 IEEE 26th International Conference on Advanced Information Networking and Applications, 299–306. Fukuoka: IEEE.
   Google Scholar
• Xu, Y., X. Liu, R. He, and Y. Chen. 2020. “Multi-Satellite Scheduling Framework and Algorithm for Very Large Area Observation.” Acta Astronautica 167:93–107. https://doi.org/10.1016/j.actaastro.2019.10.041.
   Web of Science ®Google Scholar
• Yan, Y., P. Castro, Q. Liao, and Y. Liang. 2021. “An Effective Decomposition Algorithm for Scheduling Branched Multiproduct Pipelines.” Computers & Chemical Engineering 154. https://doi.org/10.1016/j.compchemeng.2021.107494.
   Web of Science ®Google Scholar
• Zhang, Z., Y. Chen, L. He, L. Xing, and Y. Tan. 2019. “Learning-Driven Many-Objective Evolutionary Algorithms for Satellite-Ground Time Synchronization Task Planning Problem.” Swarm and Evolutionary Computation 47:72–79. https://doi.org/10.1016/j.swevo.2017.05.011.
   Web of Science ®Google Scholar
• Zhang, Z., Y. Jiang, X. Gao, and D. Huang. 2016. “An Efficient Two-Level Hybrid Algorithm for the Refinery Production Scheduling Problem Involving Operational Transitions.” Industrial & Engineering Chemistry Research 55 (28): 7768–7781. https://doi.org/10.1021/acs.iecr.6b00631.
   Web of Science ®Google Scholar