Tasks scheduling method for an agile imaging satellite based on improved ant colony algorithm

GUO Hao, QIU Di-shan, WU Guo-hua, WANG Hui-lin

Systems Engineering - Theory & Practice ›› 2012, Vol. 32 ›› Issue (11) : 2533-2539.

PDF(691 KB)
中国科学院数学与系统科学研究院期刊网
PDF(691 KB)
Systems Engineering - Theory & Practice ›› 2012, Vol. 32 ›› Issue (11) : 2533-2539. DOI: 10.12011/1000-6788(2012)11-2533

Tasks scheduling method for an agile imaging satellite based on improved ant colony algorithm

  • GUO Hao, QIU Di-shan, WU Guo-hua, WANG Hui-lin
Author information +
History +

Abstract

The observing task scheduling problem of an agile imaging satellite is studied. The scheduling model is founded considering the complex constraints as the maximal successive working duration, the attitude changing duration between tasks, energy and capacity restriction. Considering the influence among intensive observing tasks, the attitude changing duration is analyzed and a calculating method is given. An improved ant colony algorithm based on ant colony system (ACS) and max-min ant system (MMAS) is designed to solve the problem. The factors of task priority and bounds of the visible time are introduced into transfer rules. Simulation results show the efficiency of our approach.

Key words

tasks scheduling / modeling / ant colony algorithm / agile imaging satellite

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations
GUO Hao , QIU Di-shan , WU Guo-hua , WANG Hui-lin. Tasks scheduling method for an agile imaging satellite based on improved ant colony algorithm. Systems Engineering - Theory & Practice, 2012, 32(11): 2533-2539 https://doi.org/10.12011/1000-6788(2012)11-2533

References

[1] Lemaitre M, Verfaillie G, Jouhaud F, et al. Selecting and scheduling observations of agile satellites[J]. Aerospace Science and Technology, 2002, 6(5): 367-381.
[2] Cordeau F, Laporte G. ROADEF'2003 Challenge: Booklet of Abstracts[M]. France: ROADEF Society, 2003.
[3] Benoist T, Rottembourg B. Upper bounds for revenue maximization in a satellite scheduling problem[J]. 4OR: A Quarterly Journal of Operations Research, 2004, 2(3): 235-249.
[4] Pralet C, Verfaillie G. Decision upon observations and data downloads by an autonomous earth surveillance satellite[C]// The International Symposium on Artificial Intelligence, Robotics, and Automation in Space, Los Angeles: ESA, 2008: 26-29.
[5] Beaumet G, Verfaillie G. Charmeau M. Decision-making on-board an autonomous agile earth-observing satellite[EB/OL]. Scheduling and Planning Applications woRKshop, (2010-06-04)[2011-06-20]. http://decsai.ugr.es/ lcv/SPARK/08/wsProgram.html.
[6] Habet D, Vasquez M, Vimont Y. Bounding the optimum for the problem of scheduling the photographs of an agile earth observing satellite[J]. Computational Optimization and Applications, 2008, 47(2): 307-333.
[7] 廉振宇, 徐一帆, 谭跃进, 等. 灵巧卫星对地观测视场计算模型研究[EB/OL]. 测绘科学, (2010-01-01)[2010-04-12]. http://www.map.ac.cn/gkml.asp.Lian Z Y, Xu Y F, Tan Y J, et al. Computing model for earth observing field for an agile satellite[J]. Science and Surveying Mapping, (2010-01-01)[2010-04-12]. http://www.map.ac.cn/gkml.asp.
[8] Wang P, Reinelt G, Gao P, et al. A model, a heuristic and a decision support system to solve the scheduling problem of an earth observing satellite constellation[J]. Computers and Industrial Engineering, 2011, 61(2): 322-335.
[9] 贺仁杰, 李菊芳, 姚锋, 等. 成像卫星任务规划技术[M]. 北京: 科学出版社, 2011.He R J, Li J F, Yao F, et al. Mission Planning Technology of Imaging Satellites[M]. Beijing: Science Press, 2011.
[10] Dorigo M, Stutzle T. Ant Colony Optimization: Overview and Recent Advances[M]. Handbook of Metaheuristics: International Series in Operations Research and Management Science, Berlin: Springer, 2010, 146: 227-263.
[11] Wang H S. A two-phase ant colony algorithm for multi-echelon defective supply chain network design[J]. European Journal of Operational Research, 2009, 192(1): 243-252.
[12] Jovanovic R, Tuba M. An ant colony optimization algorithm with improved pheromone correction strategy for the minimum weight vertex cover problem[J]. Applied Soft Computing, 2011, 11(8): 5360-5366.
[13] Shi X H, Wang L P, Zhou Y, et al. An ant colony optimization method for prize collecting traveling saleman problem with time windows[C]// Proceedings of the 4th International Conference on Natural Computation, Shanghai: IEEE, 2008: 480-484.
[14] 李琳, 刘士新, 唐加福. 改进的蚁群算法求解带时间窗的车辆路径问题[J]. 控制与决策, 2010, 25(9): 1379-1383.Li L, Liu S X, Tang J F. Improved ant colony algorithm for solving vehicle routing problem with time windows[J]. Control and Decision, 2010, 25(9): 1379-1383.
[15] Sebbag I. Pleiades: A multi-missions concept and a partnership program[EB/OL]. French Space Agency, (2011-04-18)[2011-06-20]. http://smsc.cnes.fr/PLEIADES/.
[16] Li Y, Xu M, Wang R. Scheduling observations of agile satellites with combined genetic algorithm[C]// Proceedings the 3th International Conference on Natural Computation, Shanghai: IEEE, 2007: 29-33.
PDF(691 KB)

579

Accesses

0

Citation

Detail
Sections
Recommended

/

〈 〉