遗传算法

///Users/apple/Documents/ga/ga.xcodeproj
//  main.c
//  ga
//
//  Created by APPLE on 16/3/31.
//  Copyright © 2016年 ETaoBook. All rights reserved.
//

#include <stdio.h>
#include <stdlib.h>
#include <time.h>

#define POPSIZE 500
#define MAXIMIZATION 1
#define MINIMIZATION 2

#define Cmax 100
#define Cmin 0
//x1
#define LENGTH1 10
//x2
#define LENGTH2 10
//一个染色体
#define CHROMLENGTH LENGTH1+LENGTH2
//功能模式
int FunctionMode=MAXIMIZATION;
//群体大小
int PopSize=80;
//终止代数
int MaxGeneration=1000;
//交叉概率
double Pc=0.6;
//变异概率
double pm=0.001;


//个体
struct individual{
    double value;
    double fitness;//适应度
    char chrom[CHROMLENGTH];
};
int generation;
int best_index;
int worst_index;
struct individual bestindividual;
struct individual worstindividual;
struct individual currentbest;
struct individual population[POPSIZE];

void GenerateInitialPopulation(void);//生成初代群体
void GenerateNextPopulation(void);//生成下代群体
void EvaluatePopulation(void);//对个体进行评价
long  DecodeChromosome(char *,int,int);//解码
void CalculateObjectValue(void);//计算函数值
void  CalculateFitnessValue(void);//计算适应度
void FindBestAndWorstIndividual(void);//找到最好的个体在当前这一代
void PerformEvolution(void);
void SelectionOperator(void);//选择运算
void CrossoverOperator(void);//交叉运算
void MutationOperator(void);//变异运算
void OutputTextReport(void);


int main(void) {
    generation =0;
    GenerateInitialPopulation();
    EvaluatePopulation();
    while (generation<MaxGeneration) {
        generation++;
        GenerateNextPopulation();
        EvaluatePopulation();
        PerformEvolution();
        OutputTextReport();
    }
    
   
    return 0;
}
void GenerateInitialPopulation(void){
    int i,j;
    srand((unsigned)time(NULL));//初始化随机数生成器
    for (i=0; i<PopSize; i++) {
        for (j=0; j<CHROMLENGTH; j++) {
            population[i].chrom[j]=(rand()%10<5)?‘0‘:‘1‘;
        }
        population[i].chrom[CHROMLENGTH]=‘\0‘;
    }
    
}
void GenerateNextPopulation(void){
    SelectionOperator();
    CrossoverOperator();
    MutationOperator();
}
void EvaluatePopulation(void){
    CalculateObjectValue();//计算函数值
    CalculateFitnessValue();//计算适应度
    FindBestAndWorstIndividual();//找出最佳个体
}
long  DecodeChromosome(char *string,int point,int length){//解码染色体，得出十进制数值。

    int i;
    long decimal=0L;
    char *pointer;
    for (i=0, pointer=string+point;i<length;i++, pointer++) {
        decimal+=(*pointer-‘0‘)<<(length-1-i);
    }
    return decimal;
}

void CalculateObjectValue(void){//计算函数值
    int i;
    long temp1,temp2;
    double x1,x2;
    for (i=0; i<PopSize; i++) {
        temp1=DecodeChromosome(population[i].chrom,0 , LENGTH1);
        temp2=DecodeChromosome(population[i].chrom, LENGTH1, LENGTH2);
        x1=4.096*temp1/1023.0-2.048;
        x2=4.096*temp2/1023.0-2.048;
        population[i].value=100*(x1*x1-x2)*(x1*x1-x2)+(1-x1)*(1-x1);
        
        
    }
}
void  CalculateFitnessValue(void){//计算适应度
    int i;
    double temp = 0.0;
    for (i=0; i<PopSize; i++) {
        if (FunctionMode==MAXIMIZATION) {//如果目标是求函数最大值的优化问题
            if ((population[i].value+Cmin)>0.0) {
                temp=Cmin+population[i].value;
            }else{
                temp=0.0;
            }
        }else if (FunctionMode==MINIMIZATION){//如果目标是求函数的最小值的优化问题
            if (population[i].value<Cmax) {
                temp=Cmax-population[i].value;
            }
            else{
                temp=0.0;
            }
            
        }
        population[i].fitness=temp;
    }
}
void FindBestAndWorstIndividual(void){
    int i;
    double sum=0.0;
    bestindividual=population[0];
    worstindividual=population[0];
    for (i=1; i<PopSize; i++) {
        if (population[i].fitness>bestindividual.fitness) {
            bestindividual=population[i];
            best_index=i;
        }else if (population[i].fitness<worstindividual.fitness){
            worstindividual=population[i];
            worst_index=i;
        }
        sum+=population[i].fitness;
    }
    if (generation==0) {
        currentbest=bestindividual;
    }else{
        if (bestindividual.fitness<currentbest.fitness) {
            currentbest=bestindividual;
        }
    }
}

void PerformEvolution(void){
    if (bestindividual.fitness<currentbest.fitness) {
        currentbest=population[best_index];
    }else{
        population[worst_index]=currentbest;
    }
}
void SelectionOperator(void){//选择运算
    int i,index;
    double p,sum=0.0;
    double cfitness[POPSIZE];
    struct individual newpopulation[POPSIZE];
    for (i=0; i<PopSize; i++) {
        sum+=population[i].fitness;
    }
    for (i=0; i<PopSize; i++) {
        cfitness[i]=population[i].fitness/sum;
    }
    for (i=1; i<PopSize; i++) {
        cfitness[i]=cfitness[i-1]+cfitness[i];
    }
    for (i=0; i<PopSize; i++) {
        p=rand()%1000/1000.0;
        index=0;
        while (p>cfitness[index]) {
            index++;
        }
        newpopulation[i]=population[index];
    }
    for (i=0; i<PopSize; i++) {
        population[i]=newpopulation[i];
    }
}

void CrossoverOperator(void){//交叉算子
    int i,j;
    int index[POPSIZE];
    int point,temp;
    double p;
    char ch;
    for (i=0; i<PopSize; i++) {
        index[i]=i;
        
    }
    
    for (i=0; i<PopSize; i++) {
        point=(rand()%PopSize)-i;
        temp=index[i];
        index[i]=index[point+i];
        index[point+i]=temp;
    }
    for (i=0; i<PopSize-1; i+=2) {
        p=rand()%1000/1000.0;
        if (p<Pc) {
            point=(rand()%CHROMLENGTH-i)+1;
            for (j=point; j<CHROMLENGTH; j++) {
                ch=population[index[i]].chrom[j];
                population[index[i]].chrom[j]=population[index[i+1]].chrom[j];
                population[index[i+1]].chrom[j]=ch;
            }
        }
    }
}

void MutationOperator(void){//变异
    int i,j;
    double p;
    for (i=0; i<PopSize; i++) {
        for (j=0; j<CHROMLENGTH; j++) {
            p=rand()%1000/1000.0;
            if (p<pm) {
                population[i].chrom[j]=(population[i].chrom[j]==‘0‘)?‘1‘:‘0‘;
            }
        }
    }
}

void OutputTextReport(void){
    int i;
    double sum;
    double average;
    sum=0.0;
    for (i=0; i<PopSize; i++) {
        sum+=population[i].value;
    }
    average=sum/PopSize;
    printf("gen=%d,avg=%f,best=%f,",generation,average,currentbest.value);
    for (i=0; i<CHROMLENGTH; i++) {
        printf("%c",currentbest.chrom[i]);
    }
    printf("\n");
}