Modularity is widely used in system analysis and design such as complex engineering products and their organization, and modularity is also the key to solving optimization problems efficiently via problem decomposition. We first discover modularity in a system and then leverage this knowledge to improve the performance of the system. In this chapter, we tackle both problems with the alliance of organizational theory and evolutionary computation. First, we cluster the dependency structure matrix (DSM) of a system using a simple genetic algorithm (GA) and an information theoretic-based metric. Then we design a better GA through the decomposition of the optimization problem using the proposed DSM clustering method.