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Mission planning plays an important role in satellite control systems, especially with increase of number of satellites and more complex missions to be planned. In a general setting, the satellite mission scheduling consists in allocating tasks such as observation, communication, etc. to resources (spacecrafts (SCs), satellites, ground stations). For instance, in ground station scheduling the aim is to compute an optimal planning of communications between satellites and operations teams of Ground Station (GS). Because the communication between SCs and GSs can be done during specific window times, this problem can also be seen as a window time scheduling problem. The required communication time is usually quite smaller than the window of visibility of SCs to GSs, however, clashes are produced, making the problem highly constrained. In this work we present a Web interface for solving satellite scheduling problems through various heuristic methods. The Web interface enables the users to remotely solve their problem instances through a selection of heuristic methods such as local search methods (Hill Climbing, Simulated Annealing and Tabu Search) and population-based methods (Genetic Algorithms and variants). The user can select to solve previously generated instances by the STK simulation toolkit or generate their own problem instances. The heuristic methods are easily configurable so that users can simulate a variety of scenarios, problem sizes, etc. The execution of the heuristics methods is done at a HPC Cluster infrastructure supporting efficient execution of various solvers. Additionally, the Web application allows users to keep track of their executions as well as to share problem instances with other users.

Peer Reviewed