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中文摘要：
通过分析标准蚁群算法易于出现早熟停滞现象,该文提出一种高效收敛的算法-双态免疫优势蚁群算法.该算法将蚂蚁分成两种状态,扩大了解的搜索空间,有效抑制了收敛过程中的早熟停滞现象,将禁忌表中的抗体通过克隆扩增、高频变异等免疫算子操作得到精英蚂蚁,再对抗体记忆库引入局部最优免疫策略.针对TSP实验结果表明：该算法与最新的改进蚁群优化算法相比,其收敛速度及求解精度均得到了提高.
英文摘要：
Through an analysis of the main reason of the premature stagnation phenomenon in the standard ant colony algorithm,a highly efficient algorithm-binary state ant colony algorithm based on immunodominance algorithm （BAIA） was proposed. In order to enhance explorative capacity of the algorithm while avoiding the premature stagnation behavior,ants were divided into two groups with different state,elitist ants were got from tabu table which was optimized through immune operator like clone expansion and hyper mutation,etal,and then local optimization immunodominance operating was introduced into this algorithm. The experiments on TSP problems show that the new algorithm is capable of improving the search performance significantly no matter in convergent speed or precision.
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