论文标题
观察计划的三种多目标孟加拉算法，即活跃的AEOS
Three multi-objective memtic algorithms for observation scheduling problem of active-imaging AEOS
论文作者
论文摘要
敏捷地球观察卫星（OSPFA）的观察调度问题在敏捷地球观察卫星（AEOSS）中起着至关重要的作用。主动成像丰富了OSPFA的扩展，我们将新的问题称为具有可变图像持续时间（OSWVID）的AEO的观察调度问题。提出了累积的图像质量和详细的能耗，以将OSWVID构建为双目标优化模型。然后将三种多目标模因算法，PD+NSGA-II，LA+NSGA-II和ALNS+NSGA-II，然后设计用于求解OSWVID。考虑到我们以前的研究中总结的启发式知识，几家运营商旨在分别改进这三种算法。根据现有实例，我们根据广泛的仿真实验分析了这三种算法的关键参数优化，运算符的进化和效率。
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.
