Multi-objective approaches to ground station scheduling for optimization of communication with satellites

Abstract The ground station scheduling problem is a complex involving multiple objectives. Evolutionary techniques for multi-objective optimization are becoming popular among different fields, due to their effectiveness in obtaining set of trade-off solutions. In contrast some conventional methods, that aggregate the objectives into one weighted-sum objective function, evolutionary algorithms manage find solutions Pareto-optimal front. Selecting algorithm, however, specific adds additional challenge. this paper was solved through six algorithms, NSGA-II, NSGA-III, SPEA2, GDE3, IBEA, and MOEA/D. goal test efficacy performance number benchmark static instances problem. Benchmark sizes, allowing further testing behavior dimensionality compared recent approach by GA. results show all as good solution weighted-sum, while giving more alternatives. decomposition-based MOEA/D outperforms rest almost aspects.