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本文實例講述了C++完成簡略遺傳算法。分享給年夜家供年夜家參考。詳細完成辦法以下:
// CMVSOGA.h : main header file for the CMVSOGA.cpp //////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////// #if !defined(AFX_CMVSOGA_H__45BECA_61EB_4A0E_9746_9A94D1CCF767__INCLUDED_) #define AFX_CMVSOGA_H__45BECA_61EB_4A0E_9746_9A94D1CCF767__INCLUDED_ #if _MSC_VER > 1000 #pragma once #endif // _MSC_VER > 1000 #include "Afxtempl.h" #define variablenum 14 class CMVSOGA { public: CMVSOGA(); ~CMVSOGA(); void selectionoperator(); void crossoveroperator(); void mutationoperator(); void initialpopulation(int, int ,double ,double,double *,double *); //種群初始化 void generatenextpopulation(); //生成下一代種群 void evaluatepopulation(); //評價個別,求最好個別 void calculateobjectvalue(); //盤算目的函數值 void calculatefitnessvalue(); //盤算順應度函數值 void findbestandworstindividual(); //尋覓最好個別和最差個別 void performevolution(); void GetResult(double *); void GetPopData(CList <double,double>&); void SetFitnessData(CList <double,double>&,CList <double,double>&,CList <double,double>&); private: struct individual { double chromosome[variablenum]; //染色體編碼長度應當為變量的個數 double value; double fitness; //順應度 }; double variabletop[variablenum]; //變量值 double variablebottom[variablenum]; //變量值 int popsize; //種群年夜小 // int generation; //世代數 int best_index; int worst_index; double crossoverrate; //穿插率 double mutationrate; //變異率 int maxgeneration; //最年夜世代數 struct individual bestindividual; //最好個別 struct individual worstindividual; //最差個別 struct individual current; //以後個別 struct individual current1; //以後個別 struct individual currentbest; //以後最好個別 CList <struct individual,struct individual &> population; //種群 CList <struct individual,struct individual &> newpopulation; //新種群 CList <double,double> cfitness; //存儲順應度值 //如何使鏈表的數據是一個構造體????重要是想把種群作成鏈表。節儉空間。 }; #endif 履行文件: // CMVSOGA.cpp : implementation file // #include "stdafx.h" //#include "vld.h" #include "CMVSOGA.h" #include "math.h" #include "stdlib.h" #ifdef _DEBUG #define new DEBUG_NEW #undef THIS_FILE static char THIS_FILE[] = __FILE__; #endif ///////////////////////////////////////////////////////////////////////////// // CMVSOGA.cpp CMVSOGA::CMVSOGA() { best_index=0; worst_index=0; crossoverrate=0; //穿插率 mutationrate=0; //變異率 maxgeneration=0; } CMVSOGA::~CMVSOGA() { best_index=0; worst_index=0; crossoverrate=0; //穿插率 mutationrate=0; //變異率 maxgeneration=0; population.RemoveAll(); //種群 newpopulation.RemoveAll(); //新種群 cfitness.RemoveAll(); } void CMVSOGA::initialpopulation(int ps, int gen ,double cr ,double mr,double *xtop,double *xbottom) //第一步,初始化。 { //應當采取必定的戰略來包管遺傳算法的初始化公道,采取發生正態散布隨機數初始化?選定中間點為若干? int i,j; popsize=ps; maxgeneration=gen; crossoverrate=cr; mutationrate =mr; for (i=0;i<variablenum;i++) { variabletop[i] =xtop[i]; variablebottom[i] =xbottom[i]; } //srand( (unsigned)time( NULL ) ); //尋覓一個真實的隨機數生成函數。 for(i=0;i<popsize;i++) { for (j=0;j<variablenum ;j++) { current.chromosome[j]=double(rand()%10000)/10000*(variabletop[j]-variablebottom[j])+variablebottom[j]; } current.fitness=0; current.value=0; population.InsertAfter(population.FindIndex(i),current);//除初始化應用insertafter外,其他的用setat敕令。 } } void CMVSOGA::generatenextpopulation()//第三步,生成下一代。 { //srand( (unsigned)time( NULL ) ); selectionoperator(); crossoveroperator(); mutationoperator(); } //void CMVSOGA::evaluatepopulation() //第二步,評價個別,求最好個別 //{ // calculateobjectvalue(); // calculatefitnessvalue(); //在此步中因該按順應度值停止排序.鏈表的排序. // findbestandworstindividual(); //} void CMVSOGA:: calculateobjectvalue() //盤算函數值,應當由內部函數完成。重要由於目的函數很龐雜。 { int i,j; double x[variablenum]; for (i=0; i<popsize; i++) { current=population.GetAt(population.FindIndex(i)); current.value=0; //應用內部函數停止,在此只做成果的傳遞。 for (j=0;j<variablenum;j++) { x[j]=current.chromosome[j]; current.value=current.value+(j+1)*pow(x[j],4); } ////應用內部函數停止,在此只做成果的傳遞。 population.SetAt(population.FindIndex(i),current); } } void CMVSOGA::mutationoperator() //關於浮點數編碼,變異算子的選擇具有決議意義。 //須要guass正態散布函數,生成方差為sigma,均值為浮點數編碼值c。 { // srand((unsigned int) time (NULL)); int i,j; double r1,r2,p,sigma;//sigma高斯變異參數 for (i=0;i<popsize;i++) { current=population.GetAt(population.FindIndex(i)); //生成均值為current.chromosome,方差為sigma的高斯散布數 for(j=0; j<variablenum; j++) { r1 = double(rand()%10001)/10000; r2 = double(rand()%10001)/10000; p = double(rand()%10000)/10000; if(p<mutationrate) { double sign; sign=rand()%2; sigma=0.01*(variabletop[j]-variablebottom [j]); //高斯變異 if(sign) { current.chromosome[j] = (current.chromosome[j] + sigma*sqrt(-2*log(r1)/0.4323)*sin(2*3.1415926*r2)); } else { current.chromosome[j] = (current.chromosome[j] - sigma*sqrt(-2*log(r1)/0.4323)*sin(2*3.1415926*r2)); } if (current.chromosome[j]>variabletop[j]) { current.chromosome[j]=double(rand()%10000)/10000*(variabletop[j]-variablebottom[j])+variablebottom[j]; } if (current.chromosome[j]<variablebottom [j]) { current.chromosome[j]=double(rand()%10000)/10000*(variabletop[j]-variablebottom[j])+variablebottom[j]; } } } population.SetAt(population.FindIndex(i),current); } } void CMVSOGA::selectionoperator() //從以後個別中按幾率選擇新種群,應當加一個復制選擇,進步種群的均勻順應度 { int i,j,pindex=0; double p,pc,sum; i=0; j=0; pindex=0; p=0; pc=0; sum=0.001; newpopulation.RemoveAll(); cfitness.RemoveAll(); //鏈表排序 // population.SetAt (population.FindIndex(0),current); //過剩代碼 for (i=1;i<popsize;i++) { current=population.GetAt(population.FindIndex(i)); for(j=0;j<i;j++) //從小到年夜用before分列。 { current1=population.GetAt(population.FindIndex(j));//暫時借用變量 if(current.fitness<=current1.fitness) { population.InsertBefore(population.FindIndex(j),current); population.RemoveAt(population.FindIndex(i+1)); break; } } // m=population.GetCount(); } //鏈表排序 for(i=0;i<popsize;i++)//求順應度總值,以便歸一化,是曾經排序好的鏈。 { current=population.GetAt(population.FindIndex(i)); //掏出來的值湧現成績. sum+=current.fitness; } for(i=0;i<popsize; i++)//歸一化 { current=population.GetAt(population.FindIndex(i)); //population 有值,為何掏出來的不准確呢?? current.fitness=current.fitness/sum; cfitness.InsertAfter (cfitness .FindIndex(i),current.fitness); } for(i=1;i<popsize; i++)//幾率值從小到年夜; { current.fitness=cfitness.GetAt (cfitness.FindIndex(i-1)) +cfitness.GetAt(cfitness.FindIndex(i)); //歸一化 cfitness.SetAt (cfitness .FindIndex(i),current.fitness); population.SetAt(population.FindIndex(i),current); } for (i=0;i<popsize;)//輪盤賭幾率選擇。本段還有成績。 { p=double(rand()%999)/1000+0.0001; //隨機生成幾率 pindex=0; //遍歷索引 pc=cfitness.GetAt(cfitness.FindIndex(1)); //為何取不到數值???20060910 while(p>=pc&&pindex<popsize) //成績地點。 { pc=cfitness.GetAt(cfitness .FindIndex(pindex)); pindex++; } //必需是從index~popsize,選擇高幾率的數。即年夜於幾率p的數應當被選擇,選擇不滿則停止下次選擇。 for (j=popsize-1;j<pindex&&i<popsize;j--) { newpopulation.InsertAfter (newpopulation.FindIndex(0), population.GetAt (population.FindIndex(j))); i++; } } for(i=0;i<popsize; i++) { population.SetAt (population.FindIndex(i), newpopulation.GetAt (newpopulation.FindIndex(i))); } // j=newpopulation.GetCount(); // j=population.GetCount(); newpopulation.RemoveAll(); } //current 變更後,以上沒有成績了。 void CMVSOGA:: crossoveroperator() //非平均算術線性穿插,浮點數實用,alpha ,beta是(0,1)之間的隨機數 //對種群中兩兩穿插的個別選擇也是隨機選擇的。也可取beta=1-alpha; //current的變更會有一些轉變。 { int i,j; double alpha,beta; CList <int,int> index; int point,temp; double p; // srand( (unsigned)time( NULL ) ); for (i=0;i<popsize;i++)//生成序號 { index.InsertAfter (index.FindIndex(i),i); } for (i=0;i<popsize;i++)//打亂序號 { point=rand()%(popsize-1); temp=index.GetAt(index.FindIndex(i)); index.SetAt(index.FindIndex(i), index.GetAt(index.FindIndex(point))); index.SetAt(index.FindIndex(point),temp); } for (i=0;i<popsize-1;i+=2) {//按次序序號,順次號選擇兩個母體停止穿插操作。 p=double(rand()%10000)/10000.0; if (p<crossoverrate) { alpha=double(rand()%10000)/10000.0; beta=double(rand()%10000)/10000.0; current=population.GetAt(population.FindIndex(index.GetAt(index.FindIndex(i)))); current1=population.GetAt(population.FindIndex(index.GetAt(index.FindIndex(i+1))));//暫時應用current1取代 for(j=0;j<variablenum;j++) { //穿插 double sign; sign=rand()%2; if(sign) { current.chromosome[j]=(1-alpha)*current.chromosome[j]+ beta*current1.chromosome[j]; } else { current.chromosome[j]=(1-alpha)*current.chromosome[j]- beta*current1.chromosome[j]; } if (current.chromosome[j]>variabletop[j]) //斷定能否超界. { current.chromosome[j]=double(rand()%10000)/10000*(variabletop[j]-variablebottom[j])+variablebottom[j]; } if (current.chromosome[j]<variablebottom [j]) { current.chromosome[j]=double(rand()%10000)/10000*(variabletop[j]-variablebottom[j])+variablebottom[j]; } if(sign) { current1.chromosome[j]=alpha*current.chromosome[j]+ (1- beta)*current1.chromosome[j]; } else { current1.chromosome[j]=alpha*current.chromosome[j]- (1- beta)*current1.chromosome[j]; } if (current1.chromosome[j]>variabletop[j]) { current1.chromosome[j]=double(rand()%10000)/10000*(variabletop[j]-variablebottom[j])+variablebottom[j]; } if (current1.chromosome[j]<variablebottom [j]) { current1.chromosome[j]=double(rand()%10000)/10000*(variabletop[j]-variablebottom[j])+variablebottom[j]; } } //回代 } newpopulation.InsertAfter (newpopulation.FindIndex(i),current); newpopulation.InsertAfter (newpopulation.FindIndex(i),current1); } ASSERT(newpopulation.GetCount()==popsize); for (i=0;i<popsize;i++) { population.SetAt (population.FindIndex(i), newpopulation.GetAt (newpopulation.FindIndex(i))); } newpopulation.RemoveAll(); index.RemoveAll(); } void CMVSOGA:: findbestandworstindividual( ) { int i; bestindividual=population.GetAt(population.FindIndex(best_index)); worstindividual=population.GetAt(population.FindIndex(worst_index)); for (i=1;i<popsize; i++) { current=population.GetAt(population.FindIndex(i)); if (current.fitness>bestindividual.fitness) { bestindividual=current; best_index=i; } else if (current.fitness<worstindividual.fitness) { worstindividual=current; worst_index=i; } } population.SetAt(population.FindIndex(worst_index), population.GetAt(population.FindIndex(best_index))); //用最好的替換最差的。 if (maxgeneration==0) { currentbest=bestindividual; } else { if(bestindividual.fitness>=currentbest.fitness) { currentbest=bestindividual; } } } void CMVSOGA:: calculatefitnessvalue() //順應度函數值盤算,症結是順應度函數的設計 //current變更,這段法式變更較年夜,特殊是排序。 { int i; double temp;//alpha,beta;//順應度函數的標准變更系數 double cmax=100; for(i=0;i<popsize;i++) { current=population.GetAt(population.FindIndex(i)); if(current.value<cmax) { temp=cmax-current.value; } else { temp=0.0; } /* if((population[i].value+cmin)>0.0) {temp=cmin+population[i].value;} else {temp=0.0; } */ current.fitness=temp; population.SetAt(population.FindIndex(i),current); } } void CMVSOGA:: performevolution() //演示評價成果,有冗余代碼,current變更,法式應當轉變較年夜 { if (bestindividual.fitness>currentbest.fitness) { currentbest=population.GetAt(population.FindIndex(best_index)); } else { population.SetAt(population.FindIndex(worst_index),currentbest); } } void CMVSOGA::GetResult(double *Result) { int i; for (i=0;i<variablenum;i++) { Result[i]=currentbest.chromosome[i]; } Result[i]=currentbest.value; } void CMVSOGA::GetPopData(CList <double,double>&PopData) { PopData.RemoveAll(); int i,j; for (i=0;i<popsize;i++) { current=population.GetAt(population.FindIndex(i)); for (j=0;j<variablenum;j++) { PopData.AddTail(current.chromosome[j]); } } } void CMVSOGA::SetFitnessData(CList <double,double>&PopData,CList <double,double>&FitnessData,CList <double,double>&ValueData) { int i,j; for (i=0;i<popsize;i++) { current=population.GetAt(population.FindIndex(i)); //就由於這一句,湧現了很年夜的成績。 for (j=0;j<variablenum;j++) { current.chromosome[j]=PopData.GetAt(PopData.FindIndex(i*variablenum+j)); } current.fitness=FitnessData.GetAt(FitnessData.FindIndex(i)); current.value=ValueData.GetAt(ValueData.FindIndex(i)); population.SetAt(population.FindIndex(i),current); } FitnessData.RemoveAll(); PopData.RemoveAll(); ValueData.RemoveAll(); } # re: C++遺傳算法源法式 /******************************************************************** Filename: aiWorld.h Purpose: 遺傳算法,花朵演變。 Id: Copyright: Licence: *********************************************************************/ #ifndef AIWORLD_H_ #define AIWORLD_H_ #include <iostream> #include <ctime> #include <cstdlib> #include <cmath> #define kMaxFlowers 10 using std::cout; using std::endl; class ai_World { public: ai_World() { srand(time(0)); } ~ai_World() {} int temperature[kMaxFlowers]; //溫度 int water[kMaxFlowers]; //水質 int sunlight[kMaxFlowers]; //陽光 int nutrient[kMaxFlowers]; //營養 int beneficialInsect[kMaxFlowers]; //益蟲 int harmfulInsect[kMaxFlowers]; //益蟲 int currentTemperature; int currentWater; int currentSunlight; int currentNutrient; int currentBeneficialInsect; int currentHarmfulInsect; /** 第一代花朵 */ void Encode(); /** 花朵合適函數 */ int Fitness(int flower); /** 花朵演變 */ void Evolve(); /** 前往區間[start, end]的隨機數 */ inline int tb_Rnd(int start, int end) { if (start > end) return 0; else { //srand(time(0)); return (rand() % (end + 1) + start); } } /** 顯示數值 */ void show(); }; // ----------------------------------------------------------------- // void ai_World::Encode() // ----------------------------------------------------------------- // { int i; for (i=0;i<kMaxFlowers;i++) { temperature[i]=tb_Rnd(1,75); water[i]=tb_Rnd(1,75); sunlight[i]=tb_Rnd(1,75); nutrient[i]=tb_Rnd(1,75); beneficialInsect[i]=tb_Rnd(1,75); harmfulInsect[i]=tb_Rnd(1,75); } currentTemperature=tb_Rnd(1,75); currentWater=tb_Rnd(1,75); currentSunlight=tb_Rnd(1,75); currentNutrient=tb_Rnd(1,75); currentBeneficialInsect=tb_Rnd(1,75); currentHarmfulInsect=tb_Rnd(1,75); currentTemperature=tb_Rnd(1,75); currentWater=tb_Rnd(1,75); currentSunlight=tb_Rnd(1,75); currentNutrient=tb_Rnd(1,75); currentBeneficialInsect=tb_Rnd(1,75); currentHarmfulInsect=tb_Rnd(1,75); } // ----------------------------------------------------------------- // int ai_World::Fitness(int flower) // ----------------------------------------------------------------- // { int theFitness; theFitness=abs(temperature[flower]-currentTemperature); theFitness=theFitness+abs(water[flower]-currentWater); theFitness=theFitness+abs(sunlight[flower]-currentSunlight); theFitness=theFitness+abs(nutrient[flower]-currentNutrient); theFitness=theFitness+abs(beneficialInsect[flower]-currentBeneficialInsect); theFitness=theFitness+abs(harmfulInsect[flower]-currentHarmfulInsect); return (theFitness); } // ----------------------------------------------------------------- // void ai_World::Evolve() // ----------------------------------------------------------------- // { int fitTemperature[kMaxFlowers]; int fitWater[kMaxFlowers]; int fitSunlight[kMaxFlowers]; int fitNutrient[kMaxFlowers]; int fitBeneficialInsect[kMaxFlowers]; int fitHarmfulInsect[kMaxFlowers]; int fitness[kMaxFlowers]; int i; int leastFit=0; int leastFitIndex; for (i=0;i<kMaxFlowers;i++) if (Fitness(i)>leastFit) { leastFit=Fitness(i); leastFitIndex=i; } temperature[leastFitIndex]=temperature[tb_Rnd(0,kMaxFlowers - 1)]; water[leastFitIndex]=water[tb_Rnd(0,kMaxFlowers - 1)]; sunlight[leastFitIndex]=sunlight[tb_Rnd(0,kMaxFlowers - 1)]; nutrient[leastFitIndex]=nutrient[tb_Rnd(0,kMaxFlowers - 1)]; beneficialInsect[leastFitIndex]=beneficialInsect[tb_Rnd(0,kMaxFlowers - 1)]; harmfulInsect[leastFitIndex]=harmfulInsect[tb_Rnd(0,kMaxFlowers - 1)]; for (i=0;i<kMaxFlowers;i++) { fitTemperature[i]=temperature[tb_Rnd(0,kMaxFlowers - 1)]; fitWater[i]=water[tb_Rnd(0,kMaxFlowers - 1)]; fitSunlight[i]=sunlight[tb_Rnd(0,kMaxFlowers - 1)]; fitNutrient[i]=nutrient[tb_Rnd(0,kMaxFlowers - 1)]; fitBeneficialInsect[i]=beneficialInsect[tb_Rnd(0,kMaxFlowers - 1)]; fitHarmfulInsect[i]=harmfulInsect[tb_Rnd(0,kMaxFlowers - 1)]; } for (i=0;i<kMaxFlowers;i++) { temperature[i]=fitTemperature[i]; water[i]=fitWater[i]; sunlight[i]=fitSunlight[i]; nutrient[i]=fitNutrient[i]; beneficialInsect[i]=fitBeneficialInsect[i]; harmfulInsect[i]=fitHarmfulInsect[i]; } for (i=0;i<kMaxFlowers;i++) { if (tb_Rnd(1,100)==1) temperature[i]=tb_Rnd(1,75); if (tb_Rnd(1,100)==1) water[i]=tb_Rnd(1,75); if (tb_Rnd(1,100)==1) sunlight[i]=tb_Rnd(1,75); if (tb_Rnd(1,100)==1) nutrient[i]=tb_Rnd(1,75); if (tb_Rnd(1,100)==1) beneficialInsect[i]=tb_Rnd(1,75); if (tb_Rnd(1,100)==1) harmfulInsect[i]=tb_Rnd(1,75); } } void ai_World::show() { // cout << "/t temperature water sunlight nutrient beneficialInsect harmfulInsect/n"; cout << "current/t " << currentTemperature << "/t " << currentWater << "/t "; cout << currentSunlight << "/t " << currentNutrient << "/t "; cout << currentBeneficialInsect << "/t " << currentHarmfulInsect << "/n"; for (int i=0;i<kMaxFlowers;i++) { cout << "Flower " << i << ": "; cout << temperature[i] << "/t "; cout << water[i] << "/t "; cout << sunlight[i] << "/t "; cout << nutrient[i] << "/t "; cout << beneficialInsect[i] << "/t "; cout << harmfulInsect[i] << "/t "; cout << endl; } } #endif // AIWORLD_H_ //test.cpp #include <iostream> #include "ai_World.h" using namespace std; int main() { ai_World a; a.Encode(); // a.show(); for (int i = 0; i < 10; i++) { cout << "Generation " << i << endl; a.Evolve(); a.show(); } system("PAUSE"); return 0; }
願望本文所述對年夜家的C++法式設計有所贊助。