{"title":"Paralleling Clonal Selection Algorithm with OpenMP","authors":"Hongbing Zhu, Sicheng Chen, Jianguo Wu","doi":"10.1109/ICINIS.2010.41","DOIUrl":null,"url":null,"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.","PeriodicalId":319379,"journal":{"name":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINIS.2010.41","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.