基于改进粒子群算法的卫星数传任务调度

Abstract

Abstract: The satellite data transmission task scheduling model is established,and the constraint conditions and the scheduling objective are discussed.The adaptive scale particle swarm optimization(ASPSO) is designed,which uses decimal coding based on satellite-facility workable time windows.The particle coding represents the probability of data transmission task which can be distributed in different satellite-facility workable time windows.In this method,the population size is adjusted based on a diversity of swarms,while deleting particles with the little diversity degree and adding new particles so as to maintain population diversity.By simulation,it shows that the ASPSO excel at result and convergence in solving the satellite data transmission scheduling problem,and the values of each control parameter of the ASPSO are analyzed.

CLC Number:

TP18

CHANG Fei, WU Xiao-yue. Satellite data transmission task scheduling based on advanced particle swarm optimization[J]. Journal of Systems Engineering and Electronics, 2009, 31(10): 2404-2408.

References

[1] Howe Adele E,Whitley Darrell L,Barbulescu L,et al.Mixed initiative scheduling for the air force satellite control network[C]//2nd International NASA Workshop on Planning Scheduling for Space,2000.
[2] Gooley T D.Automating the satellite range scheduling process[D].Ohio:Air Force Institute of Technology,1993.
[3] Parish S A.A genetic algorithm approach to automating satellite range scheduling[D].Ohio-.Air Force Institute of Technology,1994.
[4] Barbulescu L,Howe A,Whitley D.AFSCN scheduling:how the problem and solution have evolved[J].Mathematical and Computer Modeling,2006,43(9):1023-1037.
[5] Zhang Na,Feng Zuren,Feng Yuanjing,et al.An optimization mode] for multisatellite resources scheduling[C]//Proc.of the 6th World Congress on Intelligent Control and Automation,Dalian,2006:7400-7404.
[6] 王远振,赵坚,聂成.多卫星一地面站系统的Petri网模型研究[J].空军工程大学学报(自然科学版),2003,4(2):7-11.
[7] 金光,武小悦,高卫斌.卫星地面站资源调度优化模型及启发式算法[J].系统工程与电子技术.2004,26(12):1839-1841.(Jin Guang,Wu Xiaoyue,Gao Weibin.Ground station resource scheduling optimization model and its heuristic algorithm[J].Systems Engineering and Electronics,2004,26(12):1839-1841.)
[8] 李云峰,武小悦.基于试探性的卫星数传任务调度算法研究[J].系统工程与电子技术,2007,29(5):764-767.(Li Yunfeng,Wu Xiaoyue.Study of tentative2based satellite data transmission tasks scheduling algorithm[J].Systems Engineering and Electronics,2007,29(5):764-767.)
[9] Kennedy J,Eberhart R.Particle swarm optimization[C]//Proc.of IEEE International Conference on Neural Networks,IEEE Service Center,Piscataway,NJ,1995.
[10] 岳超源.决策理论与方法[M].北京:科学出版社,2003:260-261.
[11] 陈德宝,赵春霞.阶梯型粒子群算法及在函数优化中的应用[J].系统仿真学报,2007,19(24):5659-5662.
[12] 李宁,邹彤,孙德宝.带时间窗车辆路径问题的粒子群算法[J].系统工程理论与实践.2004,34(4):130-135.
[13] 贾兆红,陈华平.孙耀晖.混合粒子群算法在柔性工作车间调度中的应用[J].系统仿真学报,2007,19(20):4743-4747.

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Satellite data transmission task scheduling based on advanced particle swarm optimization

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