摘 要
本文首先介绍了遗传算法的基本思想、遗传算法的构成要素、遗传算法的特点、遗
传算法的基本模型、遗传算法的应用情况及今后的研究方向等等的内容。之后是基于
Matlab 7.0 下的遗传算法求解函数最值问题。本人选择了函数优化这个应用领域，按照
遗传算法的步骤，即编码、解码、计算适应度（函数值）、选择复制运算、 交叉运算和变
异运算，对函数进行求解最值。第三部分：对遗传算法求函数最值问题的改进。这部分
主要针对本文第二部分进行改进，通过改变基本遗传算法运行参数值， 如改变交叉概率
Pc 值和变异概率 Pm 值，从而使最优值更加接近相对标准下函数的最值。
关 键 词：遗传算法 适应度 交叉概率 变异概率
Study and Application of Genetic Algorithm
Abstract ： Firstly ， the outline of the Genetic Arithmetic ， mainly introduced the Genetic
Arithmetic’s mentality、elements、specialty、fundamental model、applied situation and direction
of the following research and so on. Secondly，the problem of solving functions’ maximal and
minimum value of the Genetic Arithmetic on the basic of Matlab 7.0. As a new optimized
method，used widely in some aspects ，such as computing and science 、model identity 、
intelligence obstacles diagnoses，it is fit to solve the problems of complicated nonlinear and
multidimensioned space to find out the optimal value， which applied widely in recent years. I
choose functions perfecting and according to its steps : coding，decoding，working the adaptive
degree (function value)，selective reproductive operation，across operation，differentiation
operation and working out the maximal and minimum value. Thirdly，betterment of using the
Genetic Arithmetic to get functions’ maximal and minimum value. This part make use of
method that changing the basal Genetic Arithmetic to make maximal and minimum value
approaching the one that from opposite standard ，such as a change of probability of across
value Pc and differentiation value Pm.
Key words: Genetic Algorithm; The adaptive degree; Probability of Crossover; Probability of
Mutation
