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《Journal of Sichuan University(Engineering Science Edition)》 2009-02
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An Immune Complement Optimization Algorithm

CHEN Guang-zhu1,LI Zhi-shu2,ZHU Zhen-cai1,GONG Dun-wei3 (1.School of Mechanical and Electrical Eng.,China Univ.of Mining and Technol.,Xuzhou 221008,China; 2.School of Computer Sci.,Sichuan Univ.,Chengdu 610065,China; 3.School of Info.and Electrical Eng.,China Univ.of Mining and Technol.,Xuzhou 221008,China)  
Some immune optimization algorithms inspired by the biological immune system are lack of fast convergence speed,high robustness and are difficult for attaining the optimal solution of optimization problems.The complement system,which represents a chief component of innate immunity,not only participates in inflammation but also acts to enhance the adaptive immune response.In order to improve the capability of immune system optimization,a novel immune algorithm based on the complement activation theory-an immune complement optimization algorithm(ICOA) was presented.In ICOA,two complement operators,cleave operator and bind operator,were presented firstly.Cleave operator cleaved a complement individual into two sub-individuals,while bind operator binded two complement individuals together to form a big complement individual.Then,the optimal problem was optimized continuously through the complement operators according to the complement activation process,and the overall optimal solution was obtained.Finally,the convergence,robustness of ICOA were analyzed theoretically,which proved that ICOA could converge to the optimal solution and had high robustness.The comparison of ICOA with the classical clonal selection algorithm(CSA) showed that the optimal solution,convergence rate,robustness of ICOA were better than of CSA.
【Fund】: 国家自然科学基金资助项目(60575046);; 江苏省高校“青蓝工程”资助项目;; 中国矿业大学科技基金资助项目(200412;2006B007)
【CateGory Index】: TP18
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