中国空间科学技术（中英文）2026，Vol.46Issue(1)：73-82,10.DOI:10.16708/j.cnki.1000-758X.2026.0010
面向多星协同任务规划的自适应教学优化算法
Adaptive teaching-learning-based optimization for multi-satellite collaborative mission planning
摘要
Abstract
To address the insufficient dynamic adaptability in collaborative observation mission planning for low-earth orbit mega-constellations,an adaptive teaching-learning-based optimization algorithm was proposed.Within the teaching-learning framework,adaptive mechanisms and hybrid learning strategies were incorporated.The teaching phase was enhanced through time-varying teaching factors and an elite-guided mechanism,while the learning phase was improved using hybrid learning strategies to dynamically balance global exploration and local exploitation capabilities.Simulations demonstrated that the proposed algorithm outperformed both the improved genetic algorithm and the improved differential teaching-learning-based optimization algorithm in terms of task completion rate and computational time.In large-scale,high-complexity multi-satellite collaborative mission scenarios,it achieved 6%and 16%higher task completion rates compared to baseline algorithms,proving suitable for high-dimensional discrete optimization problems.The algorithm exhibits advantages in task completion rate,operational efficiency,and robustness,making it applicable to collaborative observation missions in low-earth orbit constellations.关键词
敏捷卫星/任务规划/多点目标/对地观测/在轨规划/教学优化算法Key words
agile satellite/mission planning/multi-point targets/earth observation/on-orbit planning/teaching-learning-based optimization algorithm分类
航空航天引用本文复制引用
刘严,刘国华,温治江,胡海鹰..面向多星协同任务规划的自适应教学优化算法[J].中国空间科学技术（中英文）,2026,46(1):73-82,10.基金项目
国家重点研发计划(2022YFB3904802) （2022YFB3904802）
