Many-objective reconfiguration of operational satellite constellations with the Large-Cluster Epsilon Non-dominated Sorting Genetic Algorithm-II

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, epsiv-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.