抽象的な

Application of Genetic Algorithm in Interplanetary Trajectory Design

S.Mahendran, ML.Mahadevan

For a given set of celestial bodies, the problem of finding an optimal sequence of gravity assist and the transfer arcs connecting the elements of the set is of combinatorial in nature. The number of possible paths grows exponentially with the number of celestial bodies. Therefore the design of an optimal gravity assist trajectory is a NP-hard mixed combinatorial continuous problem. An exhaustive search of the space of input variable is unaffordable even with modern state of art computing technology. Thus a feasible approach requires artificial intelligence (AI) and modern optimization techniques based on the intelligence selection of some potential solutions. These individuals evolve in order to generate better solution until some optimization criterion is met. Here the goal of this work is to find the trajectory which uses gravity assist maneuvers to reach the target planet (Jupiter), spending minimal fuel with minimal time for the travel. In this work, the model has been formulated, as a preliminary mission design for an interplanetary trajectory from earth to Jupiter via gravity assist at mars, which proposed to use genetic algorithm with multi objective to optimize the trajectory which has minimal fuel consumption and minimal time.

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