Monotonic Basin Hopping has been shown to be an effective method of solving low thrust trajectory optimization problems. This paper outlines an extension to the typical serial implementation by parallelizing it over any number of available compute cores. The Parallel Monotonic Basin Hopping algorithm described herein is shown to be a faster way to locate feasible solutions and improve locally optimal solutions in an automated way without requiring a feasible initial guess. The increased speed achieved through parallelization enables the algorithm to be applied to more complex problems that would otherwise be impractical for a serial implementation. Three low thrust example cases are used to demonstrate the effectiveness of the algorithm. Finally, a direct comparison between serial and parallel implementations demonstrates the expected improvement in solve time.
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