遗传算法的C语言程序案例教学提纲.docx

1、遗传算法的C语言程序案例教学提纲遗传算法的C语言程序案例遗传算法的C语言程序案例一、说明1本程序演示的是用简单遗传算法随机一个种群，然后根据所给的交叉率，变异率，世代数计算最大适应度所在的代数2演示程序以用户和计算机的对话方式执行，即在计算机终端上显示“提示信息”之后，由用户在键盘上输入演示程序中规定的命令；相应的输入数据和运算结果显示在其后。3举个例子，输入初始变量后，用y= (x1*x1)+(x2*x2)，其中-2.048=x1,x2=2.048作适应度函数求最大适应度即为函数的最大值 4程序流程图5类型定义int popsize; /种群大小 int maxgeneration; /最大

2、世代数 double pc; /交叉率 double pm; /变异率struct individual char chromchromlength+1;double value; double fitness; /适应度;int generation; /世代数int best_index;int worst_index;struct individual bestindividual; /最佳个体struct individual worstindividual; /最差个体struct individual currentbest;struct individual population

3、POPSIZE;3函数声明void generateinitialpopulation(); void generatenextpopulation();void evaluatepopulation();long decodechromosome(char *,int,int);void calculateobjectvalue();void calculatefitnessvalue();void findbestandworstindividual();void performevolution();void selectoperator();void crossoveroperator

4、();void mutationoperator();void input();void outputtextreport();6程序的各函数的简单算法说明如下：（1）void generateinitialpopulation ()和void input ()初始化种群和遗传算法参数。input() 函数输入种群大小，染色体长度，最大世代数，交叉率，变异率等参数。（2） void calculateobjectvalue();计算适应度函数值 。根据给定的变量用适应度函数计算然后返回适度值。（3）选择函数selectoperator()在函数selectoperator()中首先用rand

5、()函数产生01间的选择算子，当适度累计值不为零时，比较各个体所占总的适应度百分比的累计和与选择算子，直到达到选择算子的值那个个体就被选出，即适应度为fi的个体以fi/fk的概率继续存在；显然，个体适应度愈高，被选中的概率愈大。但是，适应度小的个体也有可 能被选中，以便增加下一代群体的多样性。（4）染色体交叉函数crossoveroperator()这是遗传算法中的最重要的函数之一，它是对个体两个变量所合成的染色体进行交叉，而不是变量染色体的交叉，这要搞清楚。首先用rand ()函数产生随机概率，若小于交叉概率，则进行染色体交叉，同时交叉次数加1。这时又要用rand()函数随机产生一位交叉位，

6、把染色体的交叉位的后面部分交叉即可；若大于交叉概率，则进行简单的染色体复制即可。（5）染色体变异函数mutation()变异是针对染色体字符变异的，而不是对个体而言，即个体变异的概率是一样。随机产生比较概率，若小于变异概率，则1变为0，0变为1，同时变异次数加1。（6）long decodechromosome(char *,int,int)本函数是染色体解码函数，它将以数组形式存储的二进制数转成十进制数，然后才能用适应度函数计算。（7）void findbestandworstindividual()本函数是求最大适应度个体的，每一代的所有个体都要和初始的最佳比较，如果大于就赋给最佳。（8）

7、void outputtextreport () 输出种群统计结果输出每一代的种群的最大适应度和平均适应度，最后输出全局最大值二、 运行环境本程序的开发工具是VC+，在VC+下运行。源代码#includestdafx.h#include #include #include /The definiton of user data 定义用户数据/#define Cmax 100 /certain maximal value#define Cmin 0 /certain minimum value#define LENGHT1 3#define LENGHT2 3/总染体长度#define CHRO

8、MLENGTH LENGHT1+LENGHT2const int MaxGeneration = 100;const int PopSize = 10;const double Pc = 0.6;const double Pm = 0.001;/ 数据结构定义/struct Individualchar chromCHROMLENGTH + 1;double value;double fitness;int generation ;int bestIndex;int worstIndex;Individual bestIndividual ;Individual worstIndividual

9、 ;/ best individual by nowIndividual currentBest ;Individual population PopSize ;/void generateInitialPopulation();void generateNextPopulation();void evalutePopulation();long decomdeChromosome(char*, int, int);void calculateObjectValue();void calculateFitnessValue();void findBestAndWorstIndividual()

10、;void performEvolution();void selectionOperator();void crossoverOperator();void mutationOperator();void outputTextReport();/以上为函数以及全局变量定义部分int main()generation = 0;generateInitialPopulation();evalutePopulation();while (generation MaxGeneration) generation+;generateNextPopulation();evalutePopulation(

11、);performEvolution();outputTextReport();system(pause);return 0;/产生第一代样本/void generateInitialPopulation() int i, j;srand(unsigned)time(NULL);for (i = 0; i PopSize; i+) for (j = 0; j CHROMLENGTH; j+) populationi.chromj = (rand() % 10) 5) ? 0 : 1;populationi.chromCHROMLENGTH =/0;/产生下一代样本 /void generate

12、NextPopulation() selectionOperator();crossoverOperator();mutationOperator();/变异算子/void mutationOperator() int i, j;double p;/ bit mutationfor (i = 0; i PopSize; i+) for (j = 0; j CHROMLENGTH; j+) p = rand() % 1000 / 1000.0;if (p Pm) populationi.chromj = (populationi.chromj = 0) ? 1: 0;/交叉算子/void cro

13、ssoverOperator() int i, j;int indexPopSize;int point, temp;double p;char ch;for (i = 0; i PopSize; i+) indexi = i;for (i = 0; i PopSize; i+) point = rand() %(PopSize - i);temp = indexi;indexi = indexpoint + i;indexpoint + i = temp;for (i = 0; i PopSize - 1; i+=2) p = rand() % 1000 / 1000.0;if (p Pc)

14、 point = rand()% (CHROMLENGTH - 1) + 1;for (j = point; j CHROMLENGTH; j+) ch = populationindexi.chromj;populationindexi.chromj = populationindexi + 1.chromj;populationindexi + 1.chromj = ch;/选择算子/void selectionOperator() int i, index;double p, sum = 0.0;double cfitnessPopSize;Individual newpopulatio

15、nPopSize;for (i = 0; i PopSize; i+) sum += populationi.fitness;for (i = 0; i PopSize; i+) cfitnessi = populationi.fitness / sum;/ calculate cumulative fitnessfor (i = 1; i PopSize; i+) cfitnessi = cfitnessi + cfitnessi - 1;for (i = 0; i cfitnessindex) index+;newpopulationi = populationindex;for (i =

16、 0; i PopSize; i+) populationi = newpopulationi; /依据某些公式对样本进行评价/void evalutePopulation() calculateObjectValue();calculateFitnessValue();findBestAndWorstIndividual(); /找出到目前为止最好的个体/void findBestAndWorstIndividual() int i;double sum = 0.0;bestIndividual = population0;worstIndividual = population0;for

17、(i = 0; i bestIndividual.fitness) bestIndividual = populationi;bestIndex = i; else if (populationi.fitness currentBest.fitness) currentBest = bestIndividual;/计算适应度/void calculateFitnessValue() int i;long temp1, temp2;double x1, x2;for (i = 0; i PopSize; i+) temp1 = decomdeChromosome(populationi.chro

18、m, 0, LENGHT1);temp2 = decomdeChromosome(populationi.chrom, LENGHT1, LENGHT2);x1 = temp1 * temp1;x2 = temp2 * temp2;populationi.fitness = x1+x2; /x1平方加上x2平方/计算目标值/目标函数为f(x) = x1* x1 + x2*x2void calculateObjectValue() int i;long temp1, temp2;double x1, x2;for (i = 0; i PopSize; i+) temp1 = decomdeChr

19、omosome(populationi.chrom, 0, LENGHT1);temp2 = decomdeChromosome(populationi.chrom, LENGHT1, LENGHT2);x1 = temp1 * temp1;x2 = temp2 * temp2;populationi.value = x1 + x2;/把二进制转化为十进制long decomdeChromosome(char* string, int point, int length) int i;long decimal = 0L;char * pointer;for(i = 0, pointer=str

20、ing+point; i length;i+,pointer+)decimal += (*pointer - 0) currentBest.fitness) currentBest = populationbestIndex; else populationworstIndex = currentBest;/打印当前样本信息/void outputTextReport() int i;double sum;double average;sum = 0.0;for (i = 0; i PopSize; i+) sum += populationi.value;average = sum / PopSize;printf(gen=%d, avg=%f, best=%f,generation, average,currentBest.value);printf( chromosome=);for( i = 0; i CHROMLENGTH; i+)printf(%c, currentBest.chromi);printf(/n);