GPU上的维度并行随机吸引策略萤火虫算法

TP311; 随机吸引策略萤火虫算法是一种元启发式优化算法.它优化了标准萤火虫算法,不仅降低了其时间复杂度,而且提高了其优化能力.高维全局优化问题的求解是一个非常耗时的过程,为了减少优化高维问题所需时间,进一步简化了随机吸引策略萤火虫算法,降低了时间复杂度,同时设计了一种维度并行策略,提出了GPU上的维度并行随机吸引策略萤火虫算法.实验结果表明,本算法保持了随机吸引策略萤火虫算法的优化能力,且加速效果明显....

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Bibliographic Details
Published in计算机工程与科学 Vol. 38; no. 10; pp. 1961 - 1966
Main Author 刘金 吴志健 吴双可 王晖 邓长寿
Format Journal Article
LanguageChinese
Published 武汉大学计算机学院,湖北武汉430072%武汉大学计算机学院,湖北武汉,430072%南昌工程学院信息工程学院,江西南昌,330099%九江学院信息科学与技术学院,江西九江,332005 2016
武汉大学软件工程国家重点实验室,湖北武汉430072
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ISSN1007-130X
DOI10.3969/j.issn.1007-130X.2016.10.002

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Summary:TP311; 随机吸引策略萤火虫算法是一种元启发式优化算法.它优化了标准萤火虫算法,不仅降低了其时间复杂度,而且提高了其优化能力.高维全局优化问题的求解是一个非常耗时的过程,为了减少优化高维问题所需时间,进一步简化了随机吸引策略萤火虫算法,降低了时间复杂度,同时设计了一种维度并行策略,提出了GPU上的维度并行随机吸引策略萤火虫算法.实验结果表明,本算法保持了随机吸引策略萤火虫算法的优化能力,且加速效果明显.
Bibliography:firefly algorithm; CUDA ; parallelization
LIU Jin1,2, WU Zhi-jian1,2 , WU Shuang-ke1,2, WANG Hui3 ,DENG Chang-shou4 (1. State Key Laboratory of Software Engineering,Wuhan University, Wuhan 430072; 2. School of Computer,Wuhan University,Wuhan 430072; 3. School of Information Engineering, Nanchang Institute of Technology, Nanehang 330099; 4. School of Information Science and Technology,Jiujiang University,Jiujiang 332005,China)
43-1258/TP
The firefly algorithm (FA) with random attraction is a metaheuristic optimization algorithm. It optimizes the standard FA, reduces the computation time complexity and improves the optimization ability of the standard FA. Solving high-dimensional global optimization problem is time consuming. So to reduce the time for solving high-dimensional global optimization problems, we simplify the firefly algorithm with random attraction further, and propose a dimension-parallel firefly algorithm with random attraction on GPU. Experimental results show that the proposed algorithm can reduce
ISSN:1007-130X
DOI:10.3969/j.issn.1007-130X.2016.10.002