AAS 99-133

Optimal Interplanetary Trajectory Design Via Hybrid Genetic Algorithm/Recursive Quadratic Program Search

T. Crain*, R. Bishop*, W. Fowler*, K. Rock**

*University of Texas, Austin, **Allied Signal, Leesburg, VA


A hybrid optimization approach is developed that combines the global search properties of genetic algorithms (GAs) with the local characteristics of recursive quadratic programming (RQP) for optimal EVE and EME ballistic trajectories. These mission classes were chosen for their potential as Mars Transhab technology demonstrators. The GA surveys the parameter space for candidate missions and provides the best candidate to the RQP module for local refinement. Initial runs provided EME solutions with Delta-V at Earth and Mars as low as 4 km/sec and 0.007 km/sec respectively, and EVE free returns with Earth Delta-V as low as 3.5 km/s.