Evolutionary optimization for computationally expensive problems
Despite all the appealing features of Evolutionary Algorithms (EAs), thousands of calls to the analysis or simulation codes are often required to locate a near optimal solution. Two major solutions for this issue are: 1) to use computationally less expensive surrogate models, and 2) to use parallel...
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Format: | Theses and Dissertations |
Language: | English |
Published: |
2009
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Online Access: | https://hdl.handle.net/10356/19262 |
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Institution: | Nanyang Technological University |
Language: | English |
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