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《Journal of Harbin Institute of Technology》 2009-07
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An improved artificial immune algorithm for multimodal optimization

XIE Jing-xin 1,2,CHENG Chun-tian3,TONG Lei-guang1(1.College of Mechanical and Electronic Engineering,Hebei Agricultural University,Baoding 071001,China;2.School of Electronic and Information Engineering,Dalian University of Technology,Dalian 116024,China;3.Dept.of Civil Engineering,Dalian University of Technology,Dalian,116024,China)  
To improve the efficiency of basic artificial immune algorithm(AIA),this paper presents an improved artificial immune algorithm(IAIA) for multimodal function optimization.Appropriate cluster analysis was conducted on real values of individuals with Euclidean distance measure,then all individuals within a cluster were considered as a group with the same concentration value.The average entropy on the whole group was calculated with binary encoding of individuals,which replaced the conventionally calculation of entropy between two individuals in AIA.To maintain high diversity,the fitness of each individual and concentration were taken into account in determining reproduction probability.Two benchmark functions were used to demonstrate the validity of IAIA and the role of each design of IAIA.Numerical experiments show that IAIA can reduce the complexity of computation,and then increases the efficiency of AIA with the maintenance of diversity and convergence in optimizing multimodal functions.
【Fund】: 国家自然科学基金资助项目(50479055)
【CateGory Index】: TP18
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