Solar sailing is a propellant-free propulsion method, leveraging the momentum of Sun-emitted photons to generate thrust. In Earth orbit, the small and constrained magnitude of the solar-sail thrust with respect to the planetary gravity
implies the need for many revolutions to accomplish an orbital transfer. Solving the resulting optimization problem requires algorithms capable of handling very large sets of decision variables. This thesis focuses on the development of a Differential Dynamic
Programming (DDP) optimization algorithm, introducing adaptive parameter tuning and novel methodologies to tackle constrained and variable-duration problems. The DDP solver is characterized (in terms of hyper-parameter sensitivity and convergence properties)
and validated against a state-of-the-art direct optimization method. The devised algorithm is applied to time-optimal Earth-centered solar-sail transfers at GEO and LEO altitudes, successfully optimizing transfer durations of up to 1000 revolutions: solutions
display distinct acceleration and drift phases, apogee reversals to optimize orbit circularization, and altitude-dependent requirements on attitude control. A variable-duration transfer problem is solved by initializing DDP using a regression performed on
the previously optimized solutions.