Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/35751
Title: Parallel evolutionary optimization with grid computing
Authors: Ng, Hee Khiang
Keywords: DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks
Issue Date: 2006
Source: Ng, H. K. (2006). Parallel evolutionary optimization with grid computing. Master’s thesis, Nanyang Technological University, Singapore.
Abstract: 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.
Description: 90 p.
URI: https://hdl.handle.net/10356/35751
DOI: 10.32657/10356/35751
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Theses

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