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Published in:
2013 | OriginalPaper | Chapter
Application of the MOAA to Satellite Constellation Refueling Optimization
Authors : Valerio Lattarulo, Jin Zhang, Geoffrey T. Parks
Published in: Evolutionary Multi-Criterion Optimization
Publisher: Springer Berlin Heidelberg
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This paper presents a satellite constellation refueling optimization problem. The design variables, composed of both serial integers and real numbers, are the refueling sequence, service time and orbital transfer time, while the objectives are the mean mission completion time and propellant consumed by orbital maneuvers. The problem is solved by a mixed-integer version of the MOAA, a recently introduced multi-objective variant of the Alliance Algorithm. This approach is compared, using the epsilon and hypervolume indicators, with a hybrid-encoding genetic algorithm (GA) composed of NSGA-II and an integer-coded GA for classical traveling salesman problems (TSP). The results show that the MOAA is able to outperform the hybrid approach based on NSGA-II by finding a better Pareto front which provides more useful information to the decision-maker.