混沌免疫混合算法参数自适应调整的优化设计

Optimization Design of Hybrid Chaos Immune Algorithm with Self-adaptive Parameter Adjusting

为提高免疫算法的求解性能,在免疫克隆选择算法中融入了混沌优化操作.分析了抗体群选择概率的重要性并给出其变化的计算式,采用抗体群的连续3代平均适应度变化率以自适应地调节抗体选择概率参数值.给出了混沌免疫混合算法参数自适应调整的优化设计的具体步骤,运用混沌免疫混合算法参数自适应调整的优化方法、免疫克隆选择算法以及其他文献方法对起重机结构主梁截面优化设计.结果表明:混沌免疫混合算法参数自适应调整的优化方法具有自适应能力强、计算效率高及优化设计精度高等优点.

In order to improve the performance of immune algorithm, chaos optimization was integrated into im- mune clone selection algorithm. The importance of the selection probability of antibody was analyzed and its varied cal- culated equation was given. The changeable rate of fitness by antibodies 3 times continuous generations was adopted to regulate antibody selection probability value adaptively. The concrete steps for the optimization method of hybrid chaosimmune algorithm with self-adaptive parameter adjusting was given. To compare the pertormance ot optlmizatmn methoO of hybrid chaos immune algorithm with self-adaptive parameter adjusting, immune clone selection algorithm and tradi- tional method in the literatures, three methods were used to optimize the main beam cross-section for crane structure. Comparison results indicate that the optimization method of hybrid chaos immune algorithm with self-adaptive parameter adjusting has many advantages such as better self-adaptive capacity, higher computation efficiency and design accuracy.