Advances in grid computing have recently sparkled the research and development of Grid problem solving environments for complex design. Parallelism in the form of distributed computing is a growing trend, particularly so in the analysis and optimization of high-fidelity computationally expensive real world design problems in science and engineering. In this paper, we present a powerful and inexpensive grid enabled evolution framework based on Globus and NetSolve toolkits for facilitating embarrassingly parallelism in hierarchical parallel evolutionary algorithms. By exploiting the grid evolution framework and a multi-level parallelization strategy of hierarchical parallel GAs, we present the evolutionary optimization of a realistic 2D aerodynamic airfoil structure. Further, we study the utility of hierarchical parallel GAs on two potential grid enabled evolution framework and analysis how it fares on a grid environment with multiple heterogeneous clusters, i.e., clusters with differing...