基于人工免疫算法的冗余传感器系统费用优化

Optimizing Cost of Redundant Multi-sensor Systems Using an Artificial Immune Algorithm

基于人类免疫系统的工作原理 ,提出了一个求解冗余多传感器系统的费用最小化问题的人工免疫算法。该算法采用免疫系统的超变异机制搜索局部区域 ;采用受体编辑机制跳出局部最小点。本算法比遗传算法和模拟退火算法更适合于解决具有很多局部最小值的冗余传感器系统费用优化的问题 ,仿真实验结果表明本算法是很有效的。

Using human immune system mechanisms, an artificial immune algorithm used for optimizing cost of redundant multi-sensor systems is presented. The artificial immune algorithm uses hyper-mutation to search local areas and receptor editing to escape from local minima. It is more suitable than simulated annealing and genetic algorithms for solving the problem that presents many local minima. Experimental results show the method is efficient.