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中文摘要：
提出一种基于抗体片段局部最优搜索的克隆选择和蚁群自适应融合算法.引入混沌扰动来增加抗体种群的多样性,以提高蚁群算法的搜索能力;利用克隆扩增、免疫基因等相关算子的操作,增强了克隆选择算法搜索的效率;通过自适应控制参数,实现了克隆选择与蚁群优化的有机结合及局部最优搜索策略的应用,加快了收敛速度,克服了抗体种群＂早熟＂问题,提高了求解精度.仿真实验结果表明,该算法具有可靠的全局收敛性,较快的收敛速度.
英文摘要：
A hybrid algorithm integrating the clone selection algorithm with the ant colony algorithm by adaptive fusion （ACALA） based on local optimization search strategy is proposed.In order to increase the diversity of the antibody and improve the search capabilities of ant algorithm,a mechanism of chaotic disturbance is introduced into this algorithm.The operation of clone expansion,immune gene,etc is adopted to enhanced the variety of antibody and affinity maturation.The adaptive control parameter is used to achieve the purpose of integrating the clone selection algorithm with the ant colony algorithm organically.Simultaneously,the proposed hybrid algorithm can prevent premature convergence effectively by taking advantage of local optimization search strategy.The results of the experiments on travelling salesman problems（TSP） show that the proposed algorithm can improve the search performance significantly no matter in convergent speed or precision.
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