IA-AIS: An improved adaptive artificial immune system applied to complex optimization problems
IA-AIS: An improved adaptive artificial immune system applied to complex optimization problems
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DOI：
10.1016/j.asoc.2011.07.014
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发表时间：
2011-12
期刊：
影响因子：
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通讯作者：
Zhonghua Li;Yunong Zhang;Hongzhou Tan
中科院分区：
文献类型：
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作者：
Zhonghua Li;Yunong Zhang;Hongzhou Tan
提出了一种改进的自适应人工免疫系统（IA-AIS）来解决连续搜索空间中的复杂优化问题。在IA-AIS优化中，对几个算子进行了改进或修正，以提高收敛速度和获得更好的最优解。进一步说，每个后代候选抗体的克隆和繁殖与其来自抗原的亲本亲和力的幂成比例;而每个后代候选抗体的突变由其来自抗原的亲本亲和力成反比指数地确定。此外，抗体之间的抑制算子根据它们的浓度被动态地控制。换句话说，抑制水平与它们在连续搜索空间中的欧几里德距离成比例。实验验证了这些改进算子的有效性。此外，建议IA-AIS优化和其他优化工具之间进行了比较研究。最后通过一个PID控制器参数整定的实例，说明了IA-AIS优化的潜在搜索能力和实用价值。
This paper proposed an improved adaptive artificial immune system (IA-AIS) for complex optimization problems in continuous search space. In this IA-AIS optimization, several operators are improved or revised which aim at faster convergence speed and better optimal solution. Further speaking, cloning and reproduction of each offspring candidate antibody are proportional to the power of its parent affinity from the antigen; while mutation of each offspring candidate antibody is inversely exponentially determined by its parent affinity from the antigen. Also, suppression operator between antibodies is dynamically controlled according to their concentration. In other words, the suppression level is proportional to their Euclidian distance in continuous search space. The effectiveness of these improvements of operators is experimentally verified. Furthermore, comparative investigations are carried out between the proposed IA-AIS optimization and other optimization utilities. Finally a persuasive case about the proportional-integral-differential (PID) controller tuning demonstrates the potential searching capability and practical value of IA-AIS optimization.