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中文摘要：
为提高人工免疫算法求解旅行商（TSP）问题的效率,提出了一种基于抗体局部最优免疫优势的克隆选择算法（Local Optimization Immunodominance Clonal Selection Algorithm）,通过局部最优免疫优势,克隆扩增,动态高频变异等相关算子的操作,提高抗体亲和度成熟的效率,同时引入浓度调节,与抗体克隆删除等操作增加抗体群的多样性,在深度搜索和广度寻优之间取得了平衡。实验结果表明：该算法在收敛速度与最优解等方面均取得了较好的效果。
英文摘要：
To enhance the efficiency of artificial immune algorithms for Traveling Salesman Problem（TSP）,a novel algorithm based on Local Optimization Immunodominance Clonal Selection Algorithm was proposed.The affinity maturation of antibody was enhanced by local Optimization Immunodominance operating,clone expansion and dynamic hyper mutation and so on.Simultaneously,adjusting mechanism of antibody concentration and antibody clonal deletion were introduced into this algorithm,which enhanced the diversity of antibody and get the balance between the depth and breadth research.Simulation testing illustrates that the algorithm has a remarkable quality of convergence velocity and global convergence reliability.
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