Many-objective reconfiguration of operational satellite constellations with the large-cluster epsilon non-dominated sorting genetic algorithm-II

Authors:
Matthew P. Ferringer;David B. Spencer;Patrick Reed
Affiliations:
The Aerospace Corporation, Chantilly, VA;Department of Aerospace Engineering, The Pennsylvania State University, University Park, PA;Department of Civil Engineering, The Pennsylvania State University, University Park, PA
Venue:
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Year:
2009

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Abstract

A general framework for the reconfiguration of satellite constellations is developed for the operational scenario when a loss of capacity has occurred and the future configuration must be constructed from the remaining assets. A multi-objective evolutionary algorithm, Ɛ-NSGA-2, adapted for use on large heterogeneous clusters, facilitated the exploration of a six-dimensional fitness landscape for several loss scenarios involving the Global Positioning System Constellation. An a posteriori decision support process was used to characterize and evaluate non-traditional but innovative constellation designs identified. The framework has enhanced design discovery and innovation for extremely complex space domain problems that have traditionally been considered computationally intractable.