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Robust scheduling for multiple agile Earth observation satellites under cloud coverage uncertainty

机译:云覆盖不确定度下的多个敏捷地球观测卫星的强大调度

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Agile satellites are the next generation of Earth observation satellites (EOSs) because they can rotate on three axes while EOSs cannot. Due to this improvement, agile EOS scheduling has attracted much attention. Meanwhile, the influence of cloud coverage for EOS is inevitable for most satellites equipped with optical remote sensing instruments, causing a significant impact on the quality of the images obtained, which therefore impacts on practical satellite scheduling. To deal with the agile satellite scheduling problem under cloud coverage uncertainty, we introduce the concept of budgeted uncertainty set and establish a linearized robust scheduling model, where the budget value should be determined by the satellite operation cost and the conservative degree. Then the original problem is transformed into a master problem and multiple pricing problems based on the column generation. Considering the enormous number of variables introduced by the dual transformation in the robust model, we propose a hybrid heuristic including column generation and simulated annealing. Finally, extensive simulation experiments are conducted to verify the effectiveness and efficiency of the proposed method.
机译:敏捷卫星是下一代地球观测卫星(eoss),因为它们可以在三轴上旋转,而eoss不能。由于这种改进,敏捷的EOS调度引起了很多关注。同时,对于大多数配备光学遥感仪器的大多数卫星的云覆盖对EOS的影响是不可避免的,对所获得的图像的质量产生显着影响,因此对实际卫星调度的影响。为了处理云覆盖率不确定性下的敏捷卫星调度问题,我们介绍了预算不确定性集的概念,并建立了一个线性化的强大调度模型,其中预算值应由卫星运营成本和保守度确定。然后,原始问题被转换为主问题和基于列生成的多重定价问题。考虑到鲁棒模型中双重转换引入的巨大变量,我们提出了一种混合启发式,包括列生成和模拟退火。最后,进行了广泛的仿真实验,以验证所提出的方法的有效性和效率。

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