Realizing the vast amount of energy available in ocean waves, an industry has emerged that is progressing towards the deployment of grid–connected wave energy converters. Likely to be deployed in arrays, a challenge to the wave energy industry is maximizing the energy production of such arrays. We have been developing a metaheuristic array optimization method specifically for the design of wave energy converter arrays. Over the last several years, we have progressed from an initial binary genetic algorithm to a real–coded genetic algorithm that has allowed us to better explore the characteristics of wave energy converter array design. We have tested the influence of minimum separation requirements, row spacing effects, passive damping for WECs, probabilistic sea states, and converter geometries. This work has been used to better understand the many influencers affecting array design and for considering the potential of wave energy to be used in emergency scenarios for coastal communities. Our work reveals the ability of our novel genetic algorithm to generate optimal layouts given a range of influencing factors.