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

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.