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An Exact Algorithm for Agile Earth Observation Satellite Scheduling with Time-Dependent Profits
Computers & Operations Research ( IF 4.6 ) Pub Date : 2020-08-01 , DOI: 10.1016/j.cor.2020.104946
Guansheng Peng , Guopeng Song , Lining Xing , Aldy Gunawan , Pieter Vansteenwegen

Abstract The scheduling of an Agile Earth Observation Satellite (AEOS) consists of selecting and scheduling a subset of possible targets for observation in order to maximize the collected profit related to the images while satisfying its operational constraints. In this problem, a set of candidate targets for observation is given, each with a time-dependent profit and a visible time window. The exact profit of a target depends on the start time of its observation, reaching its maximum at the midpoint of its visible time window. This time dependency stems from the fact that the image quality is determined by the look angle between the satellite and the target to be observed. We present an exact algorithm for the single-orbit scheduling for an AEOS considering the time-dependent profits. The algorithm is called Adaptive-directional Dynamic Programming with Decremental State Space Relaxation (ADP-DSSR). This algorithm is based on the dynamic programming approach for the Orienteering Problem with Time Windows (OPTW). Several algorithmic improvements are proposed to address the time-dependent profits. The proposed algorithm is evaluated based on extensive computational tests. The experimental results show that the algorithmic improvements significantly reduce the required computational time. The comparison between the proposed exact algorithm and a state-of-the-art heuristic illustrates that our algorithm can find the optimal solutions for sufficiently large instances within limited computational time. The results also show that our algorithm is capable of efficiently solving benchmark OPTW instances.

中文翻译:

具有时间依赖性利润的敏捷地球观测卫星调度的精确算法

摘要 敏捷地球观测卫星(AEOS)的调度包括选择和调度可能的观测目标子集,以便在满足其操作约束的同时最大化与图像相关的收集利润。在这个问题中,给出了一组观察的候选目标,每个目标都有一个时间相关的利润和一个可见的时间窗口。目标的确切利润取决于其观察的开始时间,在其可见时间窗口的中点达到最大值。这种时间依赖性源于这样一个事实,即图像质量由卫星和待观察目标之间的视角决定。我们提出了一种考虑时间相关利润的 AEOS 单轨道调度的精确算法。该算法称为具有递减状态空间松弛的自适应方向动态规划 (ADP-DSSR)。该算法基于具有时间窗口的定向运动问题 (OPTW) 的动态规划方法。提出了几种算法改进来解决与时间相关的利润。所提出的算法是基于广泛的计算测试进行评估的。实验结果表明,算法改进显着减少了所需的计算时间。所提出的精确算法与最先进的启发式算法之间的比较表明,我们的算法可以在有限的计算时间内为足够大的实例找到最佳解决方案。结果还表明,我们的算法能够有效地解决基准 OPTW 实例。
更新日期:2020-08-01
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