| 求解函数优化问题的两种异步并行算法 |
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| 引用本文： | 康卓,李艳,刘溥,康立山,陈毓屏.求解函数优化问题的两种异步并行算法[J].武汉大学学报(理学版),2002,48(1):33-36. |
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| 作者姓名： | 康卓 李艳 刘溥 康立山 陈毓屏 |
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| 作者单位： | 武汉大学,计算机学院,软件工程国家重点实验室,湖北,武汉,430072 |
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| 基金项目： | 国家自然科学基金资助 ( 70 0 710 42, 6 0 0 730 43,6 0 1330 10 ) |
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| 摘 要： | 对子空间搜索法（一类多父体重组搜索策略）与群体爬山法相结合的一种随机搜索新算法即郭涛算法的特点进行了分析与实例验证，并在此基础上提出两种异步并行算法，以适应各种类型的并行与分布计算环境。以Bump函数的优化问题为例在超级并行计算机上作了并行数值试验，得到了迄今最好的结果。
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| 关 键 词： | 郭涛算法 异步并行算法 演化算法 函数优化 并行计算 群体随机搜索算法 |
| 文章编号： | 0253-9888(2002)01-0033-04 |
Two Asynchronous Parallel Algorithms for Function Optimization |
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| KANG Zhuo,LI Yan,LIU Pu,KANG Li\|shan,CHEN Yu\|ping.Two Asynchronous Parallel Algorithms for Function Optimization[J].JOurnal of Wuhan University:Natural Science Edition,2002,48(1):33-36. |
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| Authors: | KANG Zhuo LI Yan LIU Pu KANG Li\|shan CHEN Yu\|ping |
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| Abstract: | Guo Tao proposed a stochastic search algorithm in his PhD thesis for solving function optimization problems. He combined the sub\|space search method(a general multi\|parent recombination strategy) with the population hill\|climbing method. The former keeps a global search for overall situation, and the latter keeps the convergence of the algorithm. In this paper the characteristics of the algorithm are given and some numerical experiments have been done for demostrating the efficiency of the algorithm. The Guo's algorithm has been parallelized as asynchronous parallel algorithms for suiting different parallel and distributed computing environments. The Bump problem as the numerical example is solved by a super parallel computer and some best results are obtained. |
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| Keywords: | Guo's algorithm function optimization asynchronous parallel algorithm evolutionary computation |
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