Generating optimised satellite payload operation schedules with evolutionary algorithms

Authors:
Andreas Weber;Stefanos Fasoulas;Klaus Wolf
Affiliations:
Institute of Aerospace Engineering, Technische Universität Dresden, Germany;Space Systems and Utilization, Institute of Aerospace Engineering, Technische Universität Dresden, Germany;Aircraft Engineering, Institute of Aerospace Engineering, Technische Universität Dresden, Germany
Venue:
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Year:
2009

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Abstract

An optimised schedule is vital for the operation of an interplanetary space mission. The scheduling problem of a mission with the scientific objective of reaching global coverage with more than one instrument is complex and highly restricted. Evolutionary algorithms can be an efficent method in solving scheduling problems and generating pareto-optimal alternatives. The application of an algorithm combining Evolutionary Strategy, Genetic Algorithm and Differential Evolution is demonstrated for a reference scenario of a loworbit Moon mapping mission. A reduced set of restrictions is taken into account for creating a master schedule for the operation of three different instruments for the whole mission time. An optimal set of short term operation time lines for one orbit is generated, which can be combined to a complete mission schedule. The results show that more than one year mission time can be saved with an optimised schedule.