This research describes the development and application of the Disaggregated Integral Systems Concept Optimization Technology (DISCO-Tech) methodology. DISCO-Tech is a modular space system design tool that focuses on the optimization of disaggregated and non-traditional space systems. It uses a variable-length genetic algorithm to simultaneously optimize orbital parameters, payload parameters, and payload distribution for space systems. The solutions produced by the genetic algorithm are evaluated using cost estimation, coverage analysis, and spacecraft sizing modules. A set of validation cases are presented. DISCO-Tech is then applied to three representative space mission design problems. The first problem is the design of a resilient rideshare-manifested fire detection system. This analysis uses a novel framework for evaluating constellation resilience to threats using mixed integer linear programming. A solution is identified where revisit times of under four hours are achievable for $10.5 million, one quarter of the cost of a system manifested using dedicated launches. The second problem applies the same resilience techniques to the design of an expanded GPS monitor station network. Nine additional monitor stations are identified that allow the network to continuously monitor the GPS satellites even when five of the monitor stations are inoperable. The third problem is the design of a formation of satellites for performing sea surface height detection using interferometric synthetic aperture radar techniques. A solution is chosen that meets the performance requirements of an upcoming monolithic system at 70% of the cost of the monolithic system.