CSA/IE: Novel Clonal Selection Algorithm with Information Exchange for High Dimensional Global Optimization Problems

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• 作者：Zixing Cai (1) zxcai@csu.edu.cn
  Xingbao Liu (1) bxingliu@126.com
  Xiaoping Ren (2) renxp@nim.ac.cn
• 关键词：Artificial immune systems &#8211 ; Clonal selection algorithm &#8211 ; Information exchange &#8211 ; Global optimization problems
• 刊名：Lecture Notes in Computer Science
• 出版年：2012
• 出版时间：2012
• 年：2012
• 卷：7597
• 期：1
• 页码：218-231
• 全文大小：365.4 KB
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• 作者单位：1. School of Information Science and Engineering, Central South University, Changsha, 410083 P.R. China2. National Institute of Metrology, Beijing, 100012 P.R. China
• ISSN：1611-3349

文摘

In order to increase the diversity of immune algorithm when solving high dimensional global optimization problems, a novel clonal selection algorithm with information exchange (CSA/IE) is proposed. The main characteristics of CSA/IE are clonal expansion and a novel hypermutation strategy. In addition, a simplex crossover operator is introduced to improve the ability of information exchange. Particularly, a novel performance evaluation criterion is constructed in this paper, by which the performance of different population-based algorithms can be compared easily.The experimental results indicate that CSA/IE outperforms that of the conventional clonal selection algorithms and the three DE variants, in terms of the performance evaluation criterion proposed. Finally, the proposed CSA/IE is generalized to optimize some hyper-high dimensional (such as 100~1000 dimensions) unimodal and multimodal test functions, and the results show that the proposed algorithm performs well in terms of the stability and the solution quality.