There are many types of interplanetary trajectories; e.g. 2-impulse Hohmann transfer (Mars and Venus missions) , impulsive + gravity assist (Galileo & Cassini), impulsive + low-thrust electric propulsion (Dawn, NEAR). Each type requires different methods for determining feasible trajectories. But feasibility is not sufficient. Optimization is also required to obtain the best spacecraft mass delivered to the target planet so that scientific instrumentation and/or maneuvering fuel to extend mission life can be maximized. The last 30 years have seen great improvement in the analysis and numerical methods available to optimize such trajectories. In particular, evolutionary and heuristic algorithms, such as genetic algorithms and particle swarm optimization now significantly aid mission design. Optimizing trajectories for complicated multi-flyby missions such as Galileo and Cassini, which took many person-years of work when done at JPL in the 1980’s, have been transformed by our research group into something that can be done in just a few hours on a laptop with very little a priori information, basically just a range of desired dates for departure and arrival and the type of launch vehicle that will be used.