自适应激素调节遗传算法

基于生物内分泌系统的激素调节原理,提出了一种新的自适应遗传算法。该算法以内分泌激素调节的Hill函数下降形式为基础,设计了自适应交叉算子和自适应变异算子,使交叉率和变异率在遗传算法迭代过程中,能够根据各代种群多样性的变化进行自适应调节,在整个进化过程中将种群多样性维持在合理水平。4种测试函数及三维人脑图像分割的实验结果显示,提出的自适应遗传算法可较好地保持种群多样性并克服早熟现象,性能优于其他两种自适应遗传算法及传统遗传算法。

An Adaptive Genetic Algorithm Based on Hormone Regulation

Based on the principle of hormone modulation in endocrine system, an improved adaptive genetic algorithm was proposed. This algorithm designed an adaptive crossover operator and an adaptive mutation operator based on the downward form of Hill function, to make the crossover rate and mutation rate self-regulate according to the diversity of the population in each generation, and maintain the diversity at a reasonable level in the whole process of evolution. Experimental results of 4 test functions and 3D brain image segmentation showed the improved genetic algorithm can not only effectively maintain the diversity of the population, but also avoid premature, and performances of this algorithm are better than those of the other two adaptive genetic algorithms and traditional genetic algorithm.