Abstract
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 optimization of high-fidelity computationally expensive design problems in science and engineering. In this paper, we present a powerful and inexpensive grid enabled evolution framework for facilitating 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 frameworks and analysis how it fares on a grid environment with multiple heterogeneous clusters, i.e., clusters with differing specifications and processing nodes. From the results, it is possible to conclude that a grid enabled hierarchical parallel evolutionary algorithm is not mere hype but offers a credible alternative, providing significant speed-up to complex engineering design optimization.
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Ng, HK. et al. (2005). A Multi-cluster Grid Enabled Evolution Framework for Aerodynamic Airfoil Design Optimization. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_151
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DOI: https://doi.org/10.1007/11539117_151
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28325-6
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