Genetic Algorithm with Affinity Propagation

摘要：

Classical genetic algorithm suffers heavy pressure of fitness evaluation for time-consuming optimization problems, e.g., aerodynamic design optimization, qualitative model learning in bioinformatics. To address this problem, we present a combination between genetic algorithms and clustering methods. Specifically, the clustering method used in this paper is affinity propagation. The numerical experiments demonstrate that the proposed method performs promisingly for well-known benchmark problems in the term of optimization accuracy.

关键词： genetic algorithm fitness evaluation fitness estimation

作者: Chunguo WU Hao GAO Lianjiang YU Yanchun LIANG Rongwu XIANG

作者单位: College of Computer Science and Technology,Key Laboratory for Symbol Computation and Knowledge Engin School of Basic Courses,Shenyang Pharmaceutical University,Shenyang 110016,China

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-4

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）