Complex systems, such as those encountered in aerospace engineering, can typically be considered as a hierarchy of individual coupled elements. This hierarchy is reflected in the analysis techniques that are used to analyze the physcial characteristics of the system. Consequently, a hierarchy of coupled models is to be used, accounting for different physical scales, components and/or disciplines. Numerical optimization of complex systems with embedded hierarchy is accomplished via multi-level optimization methods. Multi-level optimization methods utilize the hierarchical nature of complex systems to distribute the optimization process into smaller coupled less complex optimization problems located at the individual elements of the hierarchy. The present thesis presents a generalized approach towards decomposition and coordination for the numerical optimization of complex systems with embedded hierarchy. The developed methods are applied to numericaly maximizing the range of a supersonic business jet via multi-level optimization considering coupling between multiple engineering disciplines.