Chaos Immune Evolutionary Algorithm and Its Applications to Function Optimization
ZHANG HaiYing1, HAN GuiJin2, PAN YongXiang1
1.School of Automation, Xi’an University of Technology, Xi’an 710048 2.Department of Imformation and Control, Xi’an Institute of Post and Telecommunications, Xi’an 710121
Abstract Based on the clonal selection principle in the immune system and utilizing the ergodic property of the chaotic sequence, a chaos immune evolutionary algorithm is proposed. Firstly, the chaotic sequence is introduced into the generation of the initial population and expansion process of the antibody. Secondly, the affinity of antibody ready for expansion in the population is varied to modulate the choose probability. Finally, the algorithm is proved to be convergent by utilizing the method of probability analysis. In order to test the validity of the algorithm, it is applied to solving the problem of function optimization. Simulation experiments are made using several different functions and the results show many virtues of the algorithm, such as avoiding local optima, high precision solution and quick convergence.
ZHANG HaiYing,HAN GuiJin,PAN YongXiang. Chaos Immune Evolutionary Algorithm and Its Applications to Function Optimization[J]. , 2007, 20(2): 225-229.
[1] Wei Wei, Zhang Guohong. Artificial Immune System and Its Application in Control Field. Control Theory and Applications, 2002, 19(2): 157160 (in Chinese) (韦 魏,张国宏.人工免疫系统及其在控制系统中的应用.控制理论与应用, 2002, 19(2): 157160) [2] de Castro L N, Von Zuben F J. Learning and Optimization Using the Clonal Selection Principle. IEEE Trans on Evolutionary Computation, 2002, 6(3): 239251 [3] Mo Hongwei. The Theory of Artificial Immune System and Its Application. Harbin, China: Harbin Institute of Technology Press, 2002 (in Chinese) (莫宏伟.人工免疫系统原理与应用.哈尔滨: 哈尔滨工业大学出版社, 2002) [4] Li Bing, Jiang Weisun. Chaos Optimization Method and Its Application. Control Theory and Applications, 1997, 14(4): 613615 (in Chinese) (李 兵,蒋慰孙.混沌优化方法及其应用.控制理论与应用, 1997, 14(4): 613615) [5] Zhang Tong, Wang Hongwei, Wang Zicai. Mutative Scale Chaos Optimization Algorithm and Its Application. Control and Decision, 1999, 14(3): 285288 (in Chinese) (张 彤,王宏伟,王子才.变尺度混沌优化方法及其应用.控制与决策, 1999, 14(3): 285288) [6] Zuo Xingquan, Li Shiyong, Huang Jinjie. A New Immune Evolutionary Algorithm and Its Performance Analysis. Journal of System Simulation, 2003, 15(11): 16071609,1655 (in Chinese) (左兴权,李士勇,黄金杰.一种新的免疫进化算法及其性能分析.系统仿真学报, 2003, 15(11): 16071609,1655) [7] Li Minqiang, Kou Jisong, Lin Dan,et al. The Basic Principle and Application of Genetic Algorithm. Beijing, China:Science Press, 2002 (in Chinese) (李敏强,寇纪淞,林 丹,等.遗传算法的基本理论与应用.北京: 科学出版社, 2002) [8] de Castro L N, Timmis J I. Artificial Immune Systems as a Novel Soft Computing Paradigm. Soft Computing, 2003, 7(3): 526544 [9] Lin Dan, Li Minqiang, Kou Jisong. On the Convergence of RealCoded Genetic Algorithms. Journal of Computer Research and Development, 2000, 37(11): 13211327 (in Chinese) (林 丹,李敏强,寇纪凇. 基于实数编码的遗传算法的收敛性研究.计算机研究与发展, 2000, 37(11): 1321 1327) [10] Srinivas M, Patnaik L M. Adaptive Probabilities of Crossover and Mutation in Genetic Algorithm. IEEE Trans on Systems, Man, and Cybernetics, 1994, 24(4): 656667
2007, Vol. 20 
