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Using STK Toolkit for Evaluating a GA Base Algorithm for Ground Station Scheduling

机译:使用STK工具包评估地面站调度的GA基础算法

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The satellite scheduling and its version of ground station scheduling are increasingly attracting the attention of researchers from aerospace and optimization domain. While in the recent past satellite mission arise from large aero-spacial agencies, nowadays even smaller companies are interested in satellite missions for basic tasks such as telemetry, imaging, remote sensing, etc. The ground station scheduling problem consists in computing an optimal planning of communications between satellites or spacecraft (SC) and operations teams of Ground Station (GS). The problem is highly complex and multi-objective and in its general formulation has been shown NP-hard. Therefore, its resolution is tackled by heuristic and meta-heuristic methods. Although heuristic and meta-heuristic methods are well understood, their evaluation for specific problems, like ground station scheduling, remain a challenge. The design and development of benchmarks of instances is thus needful to evaluate such methods and also to provide the community with means to reproduce the experimental study for the same benchmark under the same or different parameter setting. In this paper, we present an XML-based benchmark of instances for the ground station scheduling generated with the STK simulation toolkit. Then we show the experimental evaluation of a Basic Genetic Algorithm using the benchmark.
机译:卫星调度及其地面站调度版本日益吸引了来自航空航天和优化领域的研究人员的关注。尽管最近的卫星任务来自大型航空航天机构,但如今,甚至更小的公司也对执行基本任务(例如遥测,成像,遥感等)的卫星任务感兴趣。地面站调度问题在于计算卫星的最优计划。卫星或航天器(SC)与地面站(GS)运营团队之间的通信。这个问题是高度复杂和多目标的,并且在其一般表述中已显示为NP难。因此,它的解决方案通过启发式和元启发式方法来解决。尽管启发式和元启发式方法已广为人知,但是它们对特定问题(如地面站调度)的评估仍然是一个挑战。因此,实例基准的设计和开发需要评估此类方法,并且还需要为社区提供手段,以在相同或不同参数设置下重现相同基准的实验研究。在本文中,我们为使用STK模拟工具包生成的地面站调度实例提供了一个基于XML的实例基准。然后,我们展示了使用基准测试对基本遗传算法的实验评估。

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