Adaptive Search Region Methods with Derivative Information in Computer Experiment
碩士 === 國立高雄大學 === 統計學研究所 === 97 === Adaptive Search Region Method (ASRM), proposed by Lai (2008), is a surrogateassisted method for searching all local extremes of a response function in a bounded experimental region. In this work, besides common assumptions for response function in computer experim...
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| Format: | Others |
| Language: | en_US |
| Published: |
2009
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| Online Access: | http://ndltd.ncl.edu.tw/handle/dd46hp |
| Summary: | 碩士 === 國立高雄大學 === 統計學研究所 === 97 === Adaptive Search Region Method (ASRM), proposed by Lai (2008), is a surrogateassisted method for searching all local extremes of a response function in a bounded experimental region. In this work, besides common assumptions for response function in computer experiments, we assume that the derivative information is also available. Thus a modified ASRM is proposed by cooperating the derivative information into surrogate construction and extreme point search. Several numerical experiments with different dimensionalities are used to show the efficiency of this new method.
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