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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/30007
標題: | 利用粒子群演算法與圖形處理器尋找最佳拉丁超立方設計 Optimizing Latin Hypercube Designs by Particle Swarm with GPU Acceleration |
作者: | Dai-Ni Hsieh 謝岱霓 |
指導教授: | 王偉仲 |
關鍵字: | 拉丁超立方設計,粒子群演算法,圖形處理器, Latin hypercube design (LHD),particle swarm optimization (PSO),graphic processing unit (GPU), |
出版年 : | 2011 |
學位: | 碩士 |
摘要: | Due to the expensive cost of many computer and physical experiments, it is important to carefully choose a small number of experimental points uniformly spreading out the experimental domain in order to obtain most information from these few runs. Although space-filling Latin hypercube designs (LHDs) are popu- lar ones that meet the need, LHDs need to be optimized to have the space-filling property. As the number of design points or variables becomes large, the to- tal number of LHDs grows exponentially. The huge number of feasible points makes this a difficult discrete optimization problem. In order to search the opti- mal LHDs efficiently, we propose a population based algorithm which is adapted from the standard particle swarm optimization (PSO) and customized for LHD. Moreover, we accelerate the adapted PSO for LHD (LaPSO) via graphic process- ing unit (GPU). According to the examined cases, the proposed LaPSO is more stable compared to other two methods and capable of improving some known results. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/30007 |
全文授權: | 有償授權 |
顯示於系所單位: | 數學系 |
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