As design exploration and optimization methods have become commonly accepted across a range of industries, such as aerospace, automotive or oil and gas, they are frequently utilized as standard practice to efficiently produce designs and aid critical engineering decisions. The widespread acceptance of these methods coupled with the power of modern computing has led to applications across a range of design problems and ever-increasing complexity. The size and scope of this expansion continually pushes the boundaries of existing exploration and optimization methods. Furthermore, a complete exploration of the optimal design space includes computationally intensive features such as multi-objective optimization, to understand the trade-off between competing objectives, and global optimization, to avoid local extrema.