基于种群熵的改进型遗传算法  

A Improved Genetic Algorithm Based on Population Entropy

作　　者：刘丽芳[1] 孟志刚[2] 张常利[1] 

机构地区：[1]太原理工大学信息工程学院,太原030024 [2]新疆大学电气工程学院,乌鲁木齐830047

出　　处：《软件》2012年第2期114-116,共3页Software

摘　　要：本文针对遗传算法具有早熟或局部收敛的缺点,根据种群熵S的实际意义,设计了一种可按照当前种群熵S的大小自动切换适应度函数的自适应适应度函数。对基本遗传算法,分别采用指数适应度函数,反比例适应度函数和本文定义的自适应适应度函数,在三种常用检测函数上进行实验,结果表明采用自适应适应度函数的基本遗传算法继承了指数适应度函数和反比例适应度函数的优点,既有强劲的收敛能力,又能保持种群多样性,可以更好更快更精确地收敛到问题的最优解。According to the practical meaning of population entropy S,this paper designs a self-adapting fitness function which could automatically select a proper fitness function according to the population entropy S now.The test conducts on three common test functions with SGA adopted exponential fitness function,inverse proportion fitness function and adaptive fitness function respectively shows that SGA with adaptive fitness function inherit the advantage of both exponential fitness function and inverse proportion fitness func-tion,and not only could search the population robustly but also could hold the variety of the population,and gets a better,more rapid and more accurate convergence to the optional solution.

关 键 词：遗传算法 种群熵S 适应度函数 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]