Journal of Systems Engineering and Electronics ›› 2009, Vol. 31 ›› Issue (10): 2404-2408.

• 系统工程 • 上一篇    下一篇

基于改进粒子群算法的卫星数传任务调度

常飞, 武小悦   

  1. 国防科技大学信息系统与管理学院, 湖南, 长沙, 410073
  • 收稿日期:2008-05-08 修回日期:2008-09-26 出版日期:2009-10-20 发布日期:2010-01-03
  • 作者简介:常飞(1982- ),男,博士研究生,主要研究方向为资源调度与组合优化.E-mail:changfei2003@163.com

Satellite data transmission task scheduling based on advanced particle swarm optimization

CHANG Fei, WU Xiao-yue   

  1. Coll. of Information Systems and Management, National Univ. of Defense Technology, Changsha 410073, China
  • Received:2008-05-08 Revised:2008-09-26 Online:2009-10-20 Published:2010-01-03

摘要: 建立了卫星数传任务调度模型,讨论了约束条件和调度目标.设计了一种自适应规模粒子群算法,该算法采用基于星地可视时间窗的十进制编码,各粒子编码表示不同可视时间窗内可分配数传作业的概率.在迭代过程中根据粒子群整体差异度动态调整种群规模,删除部分差异度小的粒子,同时增加新粒子以保证种群多样性.通过实例仿真表明,自适应规模粒子群算法在解决卫星数传任务调度问题中具有调度结果优、收敛速度快等优点,并对算法的控制参数取值进行了分析.

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.

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