Extending upon the results of the authors' previous parallel genetic algorithm optimization approach, this study investigates ways in which the parallel genetic algorithm can be used as the basis for an operational station-keeping system. Specifically, an orbit is defined an parallel genetic algorithms are applied in such a manner that the orbit is maintained within a given set of telerances. However, unlike the previous study that focused only on maintaining the orbit within the sate constraints, this study focuses on ways to maintain near-optimality in the sation keeping maneuvers, while also maintaining the operational characteristics of repeatability, speed of convergence and eas of implementation. Finally, the use of this operational station-keeping algorithm as a planning tool is discussed.
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