Una Revisión de Técnicas de Optimización Heurística para el Diseño de Trayectorias Interplanetarias en Misiones Espaciales

In this paper, heuristic optimization of interplanetary trajectories is presented. These techniques have been applied over the last two decades to the successful design of space missions in order to increase the scientific results. The multi-objective optimization problem has been solved finding a trade-off between minimizing the fuel and maximizing the useful payload of the scientific mission. A review of the literature related to the application of some evolutive strategies such as Genetic Algorithms and Differential Evolution, and Particle Swarm Optimization methods, to aerospace applications is included, in particular for the design of interplanetary exploration missions with gravity assistances. A detailed example is included to show the application of multiobjetive optimization (MOPSO) to determine the interplanetary trajectory from the Earth to the Kuiper Belt with flybys in Mars, Jupiter and Saturn.