In this work, the concept of evolutionary search is utilized as a versatile CFD solver. Specifically, a real-coded genetic algorithm, mimicking the natural evolution process, is used to minimize the residuals resulting from a finite difference discretization. While most gradient-based methods can suffer from divergence or slow convergence, the evolutionary solvers heuristic nature allows it to avoid solving the resulting systems of equations, thereby precluding many convergence difficulties and avoiding stiffness-related problems. Furthermore, these stochastic optimization techniques work...