Considering the flexible attitude maneuver and the narrow field of view of agile Earth observation satellite (AEOS) together, a comprehensive task clustering (CTC) is proposed to improve the observation scheduling problem for AEOS (OSP-FAS). Since the observation scheduling problem for AEOS with comprehensive task clustering (OSWCTC) is a dynamic combination optimization problem, two optimization objectives, the lossrate (LR) of the image quality and the energy consumption (EC), are proposed to format OSWCTC as a bi-objective optimization model. Harnessing the power of an adaptive large neighborhood search (ALNS) algorithm with a nondominated sorting genetic algorithm II (NSGA-II), a bi-objective optimization algorithm, ALNS+NSGA-II, is developed to solve OSWCTC. Based on the existing instances, the efficiency of ALNS+NSGA-II is analyzed from several aspects, meanwhile, results of extensive computational experiments are presented which disclose that OSPFAS considering CTC produces superior outcomes.

中文翻译：

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具有全面任务聚类的AEOS的观测计划问题

综合考虑灵活的姿态机动和敏捷的地球观测卫星（AEOS）的狭窄视野，提出了一种综合任务聚类（CTC）来改善AEOS的观测调度问题（OSP-FAS）。由于带有综合任务聚类的AEOS的观测计划问题（OSWCTC）是动态组合优化问题，因此提出了两个优化目标，即图像质量的损失率（LR）和能耗（EC），将OSWCTC格式化为bi目标优化模型。利用非支配排序遗传算法II（NSGA-II）的自适应大邻域搜索（ALNS）算法的功能，开发了一种双目标优化算法ALNS + NSGA-II来解决OSWCTC。根据现有实例，