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Immune and genetic hybrid optimization algorithm for data relay satellite with microwave and laser links

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Published:13 July 2019Publication History

ABSTRACT

Aiming at the problem of oversubscription of data relay access request of user stars in future Space-Based Information System, the problem of resource scheduling optimization for data relay satellite system with microwave and laser hybrid links is studied. The characteristics of the hybrid links are analyzed. A multi-objective programming model on static resource scheduling constraint satisfaction problem is established, and a hybrid optimization algorithm integration of artificial immune strategies, niche ideas and improved genetic algorithm is put forward to solve the scheduling model. Simulation results show that the hybrid optimization algorithm optimizes the model quickly, and performs well in the ability of global optimization and convergence. The results validate that the static resource scheduling model could accurately describe the microwave and laser hybrid links relay satellite system resource scheduling problem with multi-tasking and multi-type antenna1.

References

  1. Sheng Weidong, Long Yunli, Zhou Yiyu. Analysis of Target Location Accuracy in Space-Based Optical-Sensor Network. Acta Optical Sinica, 2011, 31(2): 0228001-1~7.Google ScholarGoogle ScholarCross RefCross Ref
  2. Knut Böhmer, Mark Gregory, Frank Heine, et al. Laser Communication Terminals for the European Data Relay System. Proc. of SPIE 2012, Vol. 8246: 82460D-1~7.Google ScholarGoogle ScholarCross RefCross Ref
  3. S.Rojanasoonthon, J Bard. A GRASP for parallel machine scheduling with time windows. Journal on Computing, 2005, 17(1):32--51. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. CHEN Li-jiang, WU Xiao-yue, LI Yun-feng. Scheduling Algorithm for Rlaying Satellite Based on Temporal Flexibility. Aeronautical Computing Technique, 2007,36(4):48--51.Google ScholarGoogle Scholar
  5. Wu Guohua, Ma Manhao, Wang Huilin,et al. Multi-satellite observation scheduling based on task clustering. Acta Aeronautica et Astronaution Sinica, 2011,32(7): 1275--1282.Google ScholarGoogle Scholar
  6. Wang Jun, Chen Hui-zhong, Zuo Huai-yu,et al. Pre-scheduling for Imaging Requests of Earth Observing Satellites Based on Time Ordered Acyclic Directed Graph. Acta Armamentarii, 2008, 29(5): 608--614.Google ScholarGoogle Scholar
  7. Jing Fei, Wang Jun, Li Jun, et al. A New Scheduling Method for Multi-Satellite Data Transmission Based on Squeaky-Wheel Optimization. Journal of Astronautics, 2011, 32(4): 863--870.Google ScholarGoogle Scholar
  8. Stephen Warshall. A theorem on boolean matrices. Journal of the ACM, 1962, 9(1): 11--12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. T. Bäck, D. Fogel, Z. Michalewicz, Handbook of Evolutionary Computation, Oxford Univ. Press, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. J. Horn, N. Nafpliotis, D.E. Goldberg, A niched Pareto genetic algorithm for multiobjective optimization. In Proceedings of the First IEEE Conference on Evolutionary Computation, Orlando, FL, USA, 1994.Google ScholarGoogle ScholarCross RefCross Ref
  11. L.N. de Castro, J. Timmis, An artificial immune network for multimodal function optimization. In Proceedings of the Congress on Evolutionary Computation, vol. 1, IEEE Press, Piscataway, NJ, 2002, pp. 674--699.Google ScholarGoogle Scholar

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        cover image ACM Conferences
        GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion
        July 2019
        2161 pages
        ISBN:9781450367486
        DOI:10.1145/3319619

        Copyright © 2019 ACM

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        Publication History

        • Published: 13 July 2019

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