yichuansuanfa.rar_遗传算法

#include <stdlib.h> #include <stdio.h> #include <iostream> #include <math.h> #include <time.h> using namespace std; //The Definition of Constant #define POPSIZE 100//population size //The Definition of User Data //(For different problem,there are some difference.) int PopSize=100; //population size int MaxGeneration=200; //max.number of generation double Pc=0.6; //probalility of crossover double Pm=0.001; //probalility of mutation //The definition of Data Structure struct individual //data structure of individual { char chrom[34];//a string of code representing individual int value[11]; //object value of this individual double fitness; //fitness value of this individual }; //The definition of Global Variables int CHROMLENGTH=33; int LENGTH=3; int generation; //number of generation int best_index; //index of best individual int worst_index;//index of worst individual struct individual bestindividual; //best individual of current generation struct individual worstindividual; //worst individual of current generation struct individual currentbest ; //best individual by now struct individual population [POPSIZE]; //population //Declaration of Prototype void GenerateInitialPopulation (void); void GenerateNextPopulation (void ); void EvaluatePopulation (void); long DecodeChromosome (char*,int,int); void CalculateObjectValue(void); void CalculateFitnessValue(void); void FindBestAndWorstIndividual(void); void PerformEvolution(void); void SelectionOperator(void); void CrossoverOperator(void); void MutationOperator(void); void OutputTextReport(void); //main program void main(void) { generation=0; GenerateInitialPopulation(); EvaluatePopulation(); while(generation<MaxGeneration) { generation++; GenerateNextPopulation(); EvaluatePopulation(); PerformEvolution(); OutputTextReport(); } cout<<"d11="<<currentbest.value[10]<<" "; cout<<"d10="<<currentbest.value[9]<<" "; cout<<"d9="<<currentbest.value[8]<<" "; cout<<"d8="<<currentbest.value[7]<<" "; cout<<"d7="<<currentbest.value[6]<<" "; cout<<"d6="<<currentbest.value[5]<<" "; cout<<"d5="<<currentbest.value[4]<<" "; cout<<"d4="<<currentbest.value[3]<<" "; cout<<"d3="<<currentbest.value[2]<<" "; cout<<"d2="<<currentbest.value[1]<<" "; cout<<"d1="<<currentbest.value[0]<<" "; } //Function:Generate the first population. //Variable:None void GenerateInitialPopulation(void) { int i,j; //randomize(); srand(time(0)); 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'; } } //Function; Initialize the next generation. //Variable:None. void GenerateNextPopulation(void) { SelectionOperator(); CrossoverOperator(); MutationOperator(); } //Function:Evaluate population according to certain formula. //Variable; None. void EvaluatePopulation(void) { CalculateObjectValue(); //Calculate object value CalculateFitnessValue();//calculate fitness value FindBestAndWorstIndividual();//find the best and worst individual } //Function:To decode a binary chromosome into a decimal integer. //Varible:None. //Note; The returned value may be plus,of minus. //For different coding method,this value may //be changed int "undigned int". long DecodeChromosome(char *string ,int point,int length) { int i; long decimal=0L; char*pointer; for(i=0,pointer=string+point;i<length;i++,pointer++) {if(*pointer-'0') decimal +=(long)pow(2,i); } return (decimal); } //Function :to calculate objectvalue //Variable: None. void CalculateObjectValue(void) { int i; int temp[32]; //Rosebrock function for (i=0; i<PopSize; i++) { for (int j=0;j<11;j++)//初始化 {population[i].value[j]=0;} for (int k=0;k<11;k++) //解玛 {temp[k]=DecodeChromosome(population[i].chrom,k*LENGTH,LENGTH);} for (int m=0;m<11;m++)//赋值 {if(temp[m]=0) temp[m]=20; if(temp[m]=1) temp[m]=25; if(temp[m]=2) temp[m]=32; if(temp[m]=3) temp[m]=40; if(temp[m]=4) temp[m]=50; if(temp[m]=5) temp[m]=65; if(temp[m]=6) temp[m]=80; if(temp[m]=7) temp[m]=100; } for(int l=0;l<11;l++) //赋值 {population[i].value[l]=temp[l];} } } //Function:To calculate fitness value. //Variable:None. void CalculateFitnessValue(void) { int i,a,b,t; int A[11]={0}; double temp1=0; double k0,k1,k2,k3,k4,k5,k6,k7,k8,k9,k10; for (i=0;i<PopSize; i++) { for(a=1;a<11;a++) for(b=10;b>=a;b--) {if(population[i].value[b-1]>population[i].value[b]) { t=population[i].value[b-1]; population[i].value[b-1]=t; } } for (int j=0;j<11;j++) {A[j]=population[i].value[j];} k0=A[0];k1=A[1];k2=A[2];k3=A[3];k4=A[4];k5=A[5];k6=A[6];k7=A[7];k8=A[8];k9=A[9];k10=A[10]; temp1=0.00197*(100*(pow((double)k0,1.53)+pow((double)k3,1.53)+pow((double)k1,1.53)+pow((double)k4,1.53)+ pow((double)k2,1.53)+pow((double)k5,1.53))+50*(pow((double)k7,1.53)+pow((double)k8,1.53))+160*pow((double)k6,1.53)+ 110*pow((double)k9,1.53)+90*pow((double)k10,1.53))+391/pow((double)150,1.852)*(pow((double)11,1.852*(100/pow((double)k0,4.871)+ 100/pow((double)k3,4.872)+160/pow((double)k6,4.871)+100/pow((double)k1,4.871)+100/pow((double)k4,4.871)+50/pow((double)k7,4.871)+ 100/pow((double)k2,4.871)+100/pow((double)k5,4.871)+50/pow((double)k8,4.871))+110*pow((double)22,1.852)/pow((double)k9,1.852)+ 90*pow((double)33,1.852)/pow((double)k10,4.871))); if ((pow((double)33,1.75)/pow((double)k10,4.75)*90+pow((double)22,1.75)/pow((double)k9,4.75)*110+pow((double)11,1.75)/pow((double)k6,4.75)*160+ pow((double)11,1.75)/pow((double)k3,4.75)*100+pow((double)11,1.75)/pow((double)k0,4.75)*100)<=9.4&&(pow((double)33,1.75)/pow((double)k10,4.75)*90+ pow((double)22,1.75)/pow((double)k9,4.75)*110+pow((double)11,1.75)/pow((double)k7,4.75)*50+pow((double)11,1.75)/pow((double)k4,4.75)*100+ pow((double)11,1.75)/pow((double)k1,4.75)*100)<=11.4&&(pow((double)33,1.75)/pow((double)k10,4.75)*90+pow((double)11,1.75)/pow((double)k8,4.75)*50+ pow((double)11,1.75)/pow((double)k5,4.75)*100+pow((double)11,1.75)*100)<=13.2) population[i].fitness=10000-temp1; else population[i].fitness=0; } } //Function :to find out the best individual so far current generation. //Varialbe:None. void FindBestAndWorstIndividual(void) { int i; //find out the best and worst individual of this generation bestindividual=population[0]; worstindividual=population[0]; for (i=1;i<PopSize; i++){ if (population[i].fitness>bestindividual.fitness){ bestindividual=population[i]; best_index=i; for (int j=0;j<11;j++) {bestindividual.value[j]=population[i].value[j];} } else if (population[i].fitness<worstindividual.fitness){ worstindividual=population[i]; worst_index=i; for (int k=0;k<11;k++) {worstindividual.value[k]=population[i].value[k];} } } //find out the best individual so far if (generation==0){//initialize the best individual currentbest=bestindividual; } else{ if(bestindividual.fitness>=currentbest.fitness){ currentbest=bestindividual; } } } //function:to perform evolution operation based on elitise //model.Elitist model is to replace the worst individual of this generation by the current best one. //Variable:None void PerformEvolution(void) { if (bestindividual.fitness>currentbest.fitness){ currentbest=population[best_index]; } else{ population[worst_index]=currentbest; } } //Function: to reproduce a chromosone by proportional selection, //Variable:None. void SelectionOperator(void) { int i,index; double p,sum=0.0; double cfitness[POPSIZE];//cumulative fitness value struct individual newpopulation[POPSIZE]; //calculate relative fitness