Optimization of complex systems is one of the biggest challenges in engineering. A system can be considered complex when its consisted of more sub-systems and when nonlinear interactions between its various design parameters and sub-systems are present. Optimizing such systems can be a challenge for human designers who can neither directly identify optimal design points nor manualy investigate a large design space to identify optimal solutions. In order to tackle this problem, algorithmic optimization approaches are required. Genetic algorithms can successfully navigate a large and nonlinear design space but their performance is highly dependent on the selection of various hyper-parameters. At its current form the optimization problem is concerned with the design of an electric propulsion unit for small satellites. This project aims in the development of visualization tools that will aid in better understanding such complex optimization processes. By developing visualization tools for the optimization process and the sub-systems' characteristics the algorithm's performance can be further enhanced and new insights that can prove valuable for human designers can be identified.