期刊文献+

协同进化方法求解多中心卫星任务规划问题 被引量:7

Solving Multi-center Satellite Mission Scheduling Problems by Coevolutionary Method
原文传递
导出
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。 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 co- operative 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, MC CCPSA 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.
出处 《航空学报》 EI CAS CSCD 北大核心 2010年第9期1832-1840,共9页 Acta Aeronautica et Astronautica Sinica
基金 国家自然科学基金(60604035) 国家"863"计划(2007AA12020203)
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 分治一合作 satellite center multi objective optimization cooperative coevolutlonary algorithm cooperative planning divide-and-conquer
  • 相关文献

参考文献15

  • 1Bensana E, Verfaillie G, Agnese J, et al. Exact and approximate methods for the daily management of an Earth observing satellite[C]∥Proceedings of the Symposium on Space Mission Operations and Ground Data Systems. 1996. 被引量:1
  • 2Gabrel V, Vanderpooten D. Enumeration and interactive selection of efficient paths in a multiple criteria graph for scheduling an earth observing satellite[J]. European Journal of Operational Research, 2002, 139(3): 533-542. 被引量:1
  • 3Globus A, Crawford J, Lohn J. A comparison of techniques for scheduling earth observing satellites[C]∥Proceedings of the 16th Conference on Innovative Applications of Artificial Intelligence. 2004. 被引量:1
  • 4Hall N G, Magazine M J. Maximizing the value of a space mission[J]. European Journal of Operation Research, 1994, 78(2): 224-241. 被引量:1
  • 5Vasquez M, Hao J K. Upper bounds for the SPOT 5 daily photograph scheduling problem[J]. Journal of Combinatorial Optimization, 2003, 7(1): 87-103. 被引量:1
  • 6Lin W C, Liao D Y, Liu C Y, et al. Daily imaging scheduling of an earth observation satellite[J]. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 2005, 35(2): 213-223. 被引量:1
  • 7郭玉华..多类型对地观测卫星联合任务规划关键技术研究[D].国防科学技术大学,2009:
  • 8王钧..成像卫星综合任务调度模型与优化方法研究[D].国防科学技术大学,2007:
  • 9Schetter T, Campbell M, Surka D. Multiple agent-based autonomy for satellite constellations[J]. Artificial Intelligence, 2003, 145(1-2): 147-180. 被引量:1
  • 10Das S, Knights D, Wu C, et al. Distributed intelligent planning and scheduling for enhanced spacecraft autonomy[C]∥Proceedings of the AAAI 2001 Spring Symposium Series. 2001. 被引量:1

同被引文献58

引证文献7

二级引证文献26

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部