摘要
提出了一种基于克隆选择原理的人工免疫算法(AIA),该算法中引入了克隆选择、克隆删除、受体编辑、体细胞高频变异等思想,并将其应用到广义最小生成树(GMST)的求解当中,仿真结果证明提出的免疫算法能迅速收敛到全局最优解,显著提高了全局收敛可靠性和全局收敛速度。
In this paper an Artificial Immune Algorithm(AIA) based on clonal selection principle is presented.The concepts of clone selection,clonal deletion,receptor editing and somatic hypermutation are introduced.It is applied to solving Generalized Minimum Spanning Tree(GMST).The simulation results show that AIA can converge to the global optimum solution rapidly and remarkably improve the reliability of global convergence and convergence velocity.
出处
《计算机工程与应用》
CSCD
北大核心
2005年第21期61-63,76,共4页
Computer Engineering and Applications
基金
教育部科学技术研究重点项目(教技司[2001]224号)资助
关键词
免疫算法
最小生成树
克隆选择
克隆删除
受体编辑
高频变异
immune algorithm,minimum spanning tree,clonal selection,clonal deletion,receptor editing,hypermutation
