Analysis of a hybrid genetic simulated annealing strategy applied in multi-objective optimization of orbital maneuvers

Over the several last decades, evolutionary algorithms have been widely used for parameter optimization in different engineering tasks [1]-[3]. Engineering optimization has been widely involved in aerospace sciences because of its practicality in obtaining optimal solutions to different challenging problems including dynamics and control of nonlinear systems [4]-[6]. Such fields contain different aspects of aerospace engineering including missile systems [7], unmanned aerial vehicles [8], and hypersonic aircrafts [9]. One of the problems specific to aerospace engineering is the optimization of orbital maneuvers for satellites and spacecraft [10], [11]. This problem requires heuristic search techniques in finding the optimal transfer strategy that minimizes some specific criteria like control effort [12] or fuel mass [13].

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