中国科技核心期刊

中文核心期刊

CSCD来源期刊

空间控制技术与应用 ›› 2022, Vol. 48 ›› Issue (5): 39-46.doi: 10.3969/j.issn.1674 1579.2022.05.005

• 论文与报告 • 上一篇    下一篇

多星多任务分配问题建模与优化算法研究

  

  1. 中国空间技术研究院钱学森空间技术实验室
  • 出版日期:2022-10-26 发布日期:2022-11-01
  • 基金资助:
    国家自然基金重点项目(61833009, U21B2008)和重点项目2019 JCJQ ZD 342 00

Modeling and Optimization Algorithm of Multi Task Assignment for Multi Satellite

  • Online:2022-10-26 Published:2022-11-01

摘要: 遥感卫星的多星多任务分配是一类组合优化问题,通常是将其建模为典型的优化问题,然后采用优化算法进行求解,目标是快速收敛至优化的可行解,但是每种算法都有其局限性. 针对此问题,提出了一种结合蚁群算法和模拟退火算法的多星多任务分配算法,建立具有一定通用性的优化问题模型,然后使用蚁群算法进行迭代获取多个局部最优解,最后把以上最优解作为模拟退火算法的初始解,并进行再搜索. 仿真结果表明,该算法与模拟退火算法相比具有搜索速度快的特点,同时克服了蚁群算法易陷入早熟的问题.

关键词:  , 遥感卫星, 多星任务分配, 优化建模, 蚁群算法, 模拟退火

Abstract: In the existing satellite mission planning research, most of the imaging satellite task planning problems are modeled as optimization problems, and then various intelligent optimization algorithms are used to solve them, but each algorithm has its limitations. Aiming at this problem, this paper proposes a multi satellite collaborative task planning algorithm combining the advantages of ant colony algorithm and simulated annealing algorithm. The multiple iterations of the ant colony algorithm are used to find the local optimal solution as the initial solution of the simulated annealing algorithm. The simulation results show that the proposed algorithm has certain advantages in performance compared with simulated annealing algorithm and ant colony algorithm.

Key words: remote sensing satellite, multi satellite task allocation, optimized modeling, ant colony algorithm, simulate degradation algorithm

中图分类号: 

  • V474.2