Parallel evolutionary optimization with grid computing
90 p.
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2010
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sg-ntu-dr.10356-357512023-03-04T00:44:21Z Parallel evolutionary optimization with grid computing Ng, Hee Khiang Ong Yew Soon School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks 90 p. A rising trend in science and engineering is in the utilization of increasingly highfidelity and accurate analysis codes in the design analysis and optimization process. In many application areas such as photonics, electromagnetics, aerospace, biomedical, micro-electro-mechanical systems and coupled-field multidisciplinary system design processes, simulation procedures involving Computational Structural Mechanics (CSM), Computational Fluid Dynamics (CFD) or Computational Electronics and Electromagnetics (CEE) are an important step in the design process. The time taken for these processes generally varies from many minutes to hours or days of supercomputing time. This often leads to high computing costs in the design optimization process, hence a much longer design cycle time to locate a near optimum design solution. This thesis presents a Gridenabled scalable parallel evolutionary framework for solving computationally expensive optimization problems under limited time budget. MASTER OF ENGINEERING (SCE) 2010-04-23T01:32:32Z 2010-04-23T01:32:32Z 2006 2006 Thesis Ng, H. K. (2006). Parallel evolutionary optimization with grid computing. Master’s thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/35751 10.32657/10356/35751 application/pdf |
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DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks Ng, Hee Khiang Parallel evolutionary optimization with grid computing |
description |
90 p. |
author2 |
Ong Yew Soon |
author_facet |
Ong Yew Soon Ng, Hee Khiang |
format |
Theses and Dissertations |
author |
Ng, Hee Khiang |
author_sort |
Ng, Hee Khiang |
title |
Parallel evolutionary optimization with grid computing |
title_short |
Parallel evolutionary optimization with grid computing |
title_full |
Parallel evolutionary optimization with grid computing |
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Parallel evolutionary optimization with grid computing |
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Parallel evolutionary optimization with grid computing |
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parallel evolutionary optimization with grid computing |
publishDate |
2010 |
url |
https://hdl.handle.net/10356/35751 |
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1759854153545285632 |