Paralleling Clonal Selection Algorithm with OpenMP

Hongbing Zhu, Sicheng Chen, Jianguo Wu
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引用次数: 5

Abstract

Clonal selection algorithm (CSA) is one of the most representative Immune algorithms (IA) and was applied into the protein structure prediction (PSP) on AB off-lattice model, but it required a long time in the calculation. So in this paper, a parallel clonal selection algorithm (CSA) was proposed, which was implemented using distributed computing model that employed Open MP on four core computer. In the algorithm, several sub-populations replaced the original single population, and each sub-population evolved independently, and the current best individual was distributed into all the sub-populations. The parallel algorithm overcame premature convergence and found global optima efficiently. And the experiment results shown that the performance had beensignificantly improved.
基于OpenMP的并行克隆选择算法
克隆选择算法(CSA)是最具代表性的免疫算法(IA)之一,已应用于AB离晶格模型的蛋白质结构预测(PSP),但其计算时间较长。为此,本文提出了一种并行克隆选择算法(CSA),并在四核计算机上采用Open MP分布式计算模型实现该算法。在该算法中,多个子种群取代原有的单个种群,每个子种群独立进化,并将当前最优个体分配到所有子种群中。并行算法克服了早熟收敛,有效地找到了全局最优解。实验结果表明,该系统的性能得到了显著提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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