Journal Article10.1016/J.FUTURE.2006.10.008
Efficient Hierarchical Parallel Genetic Algorithms using Grid computing
TL;DR: An empirical study on GE-HPGA using a benchmark problem and a realistic aerodynamic airfoil shape optimization problem for diverse Grid environments having different communication protocols, cluster sizes, processing nodes, at geographically disparate locations indicates that the proposed GE- HPGA offers a credible framework for providing a significant speed-up to evolutionary design optimization in science and engineering.
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About: This article is published in Future Generation Computer Systems. The article was published on 01 May 2007. The article focuses on the topics: Grid computing & GridRPC.
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Citations
Bio-inspired computation: Where we stand and what's next
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References
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Genetic algorithms in search, optimization, and machine learning
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TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
The GRID: Blueprint for a New Computing Infrastructure
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Validity of the single processor approach to achieving large scale computing capabilities
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