航空学报 > 2010, Vol. 31 Issue (9): 1832-1840

协同进化方法求解多中心卫星任务规划问题

王冲, 景宁, 李军, 王钧   

  1. 国防科学技术大学 电子科学与工程学院
  • 收稿日期:2009-09-27 修回日期:2010-02-26 出版日期:2010-09-25 发布日期:2010-09-25
  • 通讯作者: 李军

Solving Multi-center Satellite Mission Scheduling Problems by Coevolutionary Method

Wang Chong, Jing Ning, Li Jun, Wang Jun   

  1. College of Electronic Science and Engineering, National University of Defense Technology
  • Received:2009-09-27 Revised:2010-02-26 Online:2010-09-25 Published:2010-09-25
  • Contact: Li Jun

摘要: 在分析多卫星中心内部特点及中心间关系的基础上建立了多中心协同规划问题(MCCOPP)的数学模型,提出了解决该问题的多中心合作协同进化规划算法(MCCCSPA)。MCCCSPA基于分治-合作策略,根据中心数目以及观测目标集合特点将观测目标分解分配至各中心;提出等长扩展二进制染色体编码方式有效表达问题的解,便于个体的交叉、变异、合作操作;并综合多中心个体代表合作求解本中心个体适应值;其中交叉、变异、合作算子在确保可行解的前提下保证各中心子种群的多样性、加快收敛速度。仿真实验及分析结果表明:该方法能够有效解决多中心协同的卫星任务规划问题。

关键词: 卫星中心, 多目标优化, 合作协同进化规划算法, 协同规划, 分治-合作

Abstract: A multi-center cooperative planning problem (MCCOPP) model is constructed which takes into consideration the characteristics of multiple satellite centers and the relations among them. Then a multi-center cooperative coevolutionary planning and scheduling algorithm (MCCCPSA) is proposed. Considering the number of the multi-centers and the characteristics of the observed targets, MCCCPSA decomposes the targets into smaller components and assigns them to each center based on the divide-and-conquer strategy. Moreover, MCCCPSA adopts an extended constant length binary representation to chromosomes, which effectively facilitates the crossover, mutation and cooperation operations. The individual fitness in each center is calculated in collaboration with the representatives of other centers. Furthermore, the crossover, mutation and cooperation operators ensure the feasibility and diversity of the child population while accelerating the convergence. Simulation and analysis show that the proposed algorithm can solve the problems effectively.

Key words: satellite center, multi-objective optimization, cooperative coevolutionary algorithm, cooperative planning, divide-and-conquer

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