Optimal Rendezvous Trajectory Using a Hybrid Approach

Abstract — Genetic algorithms have gained popularity as effective search procedures for obtaining solutions to traditionally difficult space mission optimization problems. In this paper, a real-coded genetic algorithm is used together with calculus of variations to optimize a trajectory for rendezvous problem. The global search properties of genetic algorithm combine with the local search capabilities of calculus of variations to produce solutions that are superior to those generated with the calculus of variations alone, and these solutions require less user interaction than previously possible. The genetic algorithm is not hampered by ill-behaved gradients and is relatively insensitive to problems with a small radius of convergence. The use of calculus of variations within the genetic algorithm optimization routine increases the precision of the final solution to levels uncommon for a genetic algorithm alone