摘要
针对简单遗传算法中线性适应度函数随进化过程恒定不变的缺点,提出一种可随进化代数动态调整的非线性适应度函数。以典型的遗传算法测试函数为算例,分别以Goldberg提出的线性拉伸方法[1]与文中提出的改进遗传算法进行计算。计算结果表明文中提出的动态适应度函数对简单遗传算法的改进有较明显的效果。
Aiming at the shortcoming of the simple genetic algorithm（GA） with the linear fitness function unfit for evolutionary proeess,a modified genetic algorithm with the nonlinear fitness function,which can adapt to evolutionary process of algorithm is presented in this dissertation. GA with linear scaling method proposed by Goldberg and modified GA in this paper, respectively, calculates the genetic algorithm＇s testing functions. The comparison between the results obtained by above-mentioned algorithms indicates that the nonlinear adaptive fitness function is effective for improving the simple genetic algorithm＇s performance.
出处
《计算机应用与软件》
CSCD
北大核心
2006年第2期108-110,共3页
Computer Applications and Software
