Observation scheduling problem for agile earth observation satellites (OSPFAS) plays a critical role in management of agile earth observation satellites (AEOSs). Active imaging enriches the extension of OSPFAS, we call the novel problem as observation scheduling problem for AEOS with variable image duration (OSWVID). A cumulative image quality and a detailed energy consumption is proposed to build OSWVID as a bi-objective optimization model. Three multi-objective memetic algorithms, PD+NSGA-II, LA+NSGA-II and ALNS+NSGA-II, are then designed to solve OSWVID. Considering the heuristic knowledge summarized in our previous research, several operators are designed for improving these three algorithms respectively. Based on existing instances, we analyze the critical parameters optimization, operators evolution, and efficiency of these three algorithms according to extensive simulation experiments.
翻译：灵活地球观测卫星(OSPFAS)的观测时间安排问题在管理灵活地球观测卫星(AEOSs)方面发挥着关键作用。主动成像丰富了OSPIS的扩展,我们称这个新问题为具有可变图像持续期的AEOS(OSWVID)的观测时间安排问题。为了将OSWVID建成一个双目标优化模型,建议采用一个累积图像质量和详细能源消耗模型,将OSWVID建成一个双目标优化模型。然后设计出三种多目标的计量算法,即PD+NSGA-II、LA+NSGA-II和ALNS+NSGA-II,目的是解决OSWVID。考虑到我们以往研究中总结的超常知识,我们设计了几个操作者分别改进这三种算法。我们根据现有实例,根据广泛的模拟实验,分析了这三种算法的关键参数的优化、操作者演进和效率。
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