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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.
This paper proposes a clone selection and ant colony adaptive fusion algorithm based on the local optimal search of antibody fragments.The chaotic perturbation is introduced to increase the diversity of antibody populations to improve the search ability of ant colony algorithm.The use of clonal amplification and immune genes and other related The operation of the operator enhances the search efficiency of the clonal selection algorithm. Through the adaptive control parameters, the organic combination of clonal selection and ant colony optimization and the application of local optimal search strategy are realized, which speeds up the convergence and overcomes the problem of antibody population “Premature” problem, which improves the accuracy of the solution.The simulation results show that this algorithm has reliable global convergence and fast convergence speed.