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针对遗传算法难以解决多峰函数优化的问题,提出一种基于双变异算子的免疫网络算法.该算法借鉴免疫系统的克隆选择和免疫网络理论,采用双变异算子提高算法的全局和局部搜索能力.利用动态网络抑制策略保持种群的多样性,自适应地调节抗体群的规模.仿真结果表明,该算法能有效地改善种群的多样性,较好地实现全局优化与局部优化的有机结合,具有更强的多峰函数优化能力.
In order to solve the problem of multi-peak function optimization which is difficult to be solved by genetic algorithm, an immune network algorithm based on double mutation operator is proposed. This algorithm draws on the clonal selection and immune network theory of immune system and adopts double mutation operator to improve the global and local search Ability.The dynamic network suppression strategy is used to keep the diversity of the population and adjust the size of the antibody population adaptively.The simulation results show that the algorithm can effectively improve the diversity of the population and better realize the organic combination of global optimization and local optimization, With more multi-peak function optimization ability.