?? genetic.cpp
字號:
//頭文件: Genetic.hpp
//目的: 為遺傳算法提供基類,該基類將評價函數值直接作為適合度,采用
// 新個體直接替換老個體的整體再生法
//語言: VC++ 6.0
//時間: 1999年7月
//作者: 劉康
//環境: Win32
//注意: EvalVal(INDIVIDUAL&)應由用戶類覆蓋,以提供正確的評價函數.
//////////////////////////////////////////////////////////////////////
#include <stdlib.h>
#include "Genetic.hpp"
//////////////////////////////////////////////////////////////////////
// Construction/Destruction
//////////////////////////////////////////////////////////////////////
Genetic::Genetic()
{
IndNumber = 0;
GeneLen = 0;
Elitism = ELITISM;
Cross = ONE_POINT;
Parameter = GEN_FIXED;
OperatorFit[0]=60; OperatorFit[1]=OperatorFit[0]+40;
OperatorStart[0] = 70; OperatorStart[1] = 30;
OperatorEnd[0] = 50; OperatorEnd[1] = 50;
CrossProb = 0.8;
MutProb = 0.01;
ElitismProb = 0.1;
CurrentChild = 0;
ChildrenNum = IndNumber;
Individual = 0;
Children = 0;
IndIndex = 0;
FitIndex = 0;
Communication = NULL;
}
Genetic::Genetic(int n, int gl)
{
IndNumber = n;
GeneLen = gl;
Elitism = ELITISM;
Cross = ONE_POINT;
Parameter = GEN_FIXED;
OperatorFit[0]=60; OperatorFit[1]=OperatorFit[0]+40;
OperatorStart[0] = 70; OperatorStart[1] = 30;
OperatorEnd[0] = 50; OperatorEnd[1] = 50;
CrossProb = 0.8;
MutProb = 0.01;
ElitismProb = 0.1;
CurrentChild = 0;
ChildrenNum = IndNumber;
IndInit();
Communication = NULL;
}
Genetic::Genetic(Genetic& g)
{
Elitism = g.Elitism;
Cross = g.Cross;
Parameter = g.Parameter;
OperatorFit[0] = g.OperatorFit[0];
OperatorFit[1] = g.OperatorFit[1];
OperatorStart[0] = g.OperatorStart[0];
OperatorStart[1] = g.OperatorStart[1];
OperatorEnd[0] = g.OperatorEnd[0];
OperatorEnd[1] = g.OperatorEnd[1];
CrossProb = g.CrossProb;
MutProb = g.MutProb;
IndNumber = g.IndNumber;
GeneLen = g.GeneLen;
CurrentChild = g.CurrentChild;
ChildrenNum = g.ChildrenNum;
ElitismProb = g.ElitismProb;
Communication = g.Communication;
IndInit();
for(int i=0; i<IndNumber; i++)
{
Individual[i].Chrom = g.Individual[i].Chrom;
Individual[i].Fit = g.Individual[i].Fit;
Individual[i].Val = g.Individual[i].Val;
FitIndex[i] = g.FitIndex[i];
IndIndex[i] = g.IndIndex[i];
}
}
Genetic::~Genetic()
{
if(Individual) delete []Individual;
if(Children) delete []Children;
if(IndIndex) delete []IndIndex;
if(FitIndex) delete []FitIndex;
}
//設置個體數和個體長度
void Genetic::SetNumLen(int IndN, int GLen)
{
if(Individual) delete []Individual;
if(Children) delete []Children;
if(IndIndex) delete []IndIndex;
if(FitIndex) delete []FitIndex;
IndNumber = IndN;
GeneLen = GLen;
ChildrenNum = IndNumber;
IndInit();
}
//個體初始化
bool Genetic::IndInit()
{
Individual = new INDIVIDUAL[IndNumber];
Children = new INDIVIDUAL[IndNumber];
IndIndex = new int[IndNumber];
FitIndex = new double[IndNumber];
if(Individual && Children && IndIndex && FitIndex)
{
for(int i=0; i<IndNumber; i++)
{
Individual[i].Chrom.SetLen(GeneLen);
Children[i].Chrom.SetLen(GeneLen);
IndIndex[i] = i;
}
return true;
}
else return false;
}
//計算總適合度
void Genetic::CalFitIndex()
{
double allfit = 0;
for(int i=0; i<IndNumber; i++)
{
allfit += Individual[i].Fit-Individual[IndIndex[IndNumber-1]].Fit;
FitIndex[i] = allfit;
}
}
//設置交叉變異適合度
void Genetic::SetOperator(double c, double m)
{
OperatorFit[0] = c;
OperatorFit[1] = OperatorFit[0]+m;
}
//設置標志集
void Genetic::SetFlags(CROSS_METHOD c, ELITISM_METHOD e, PARAMETER_METHOD p)
{
Cross = c;
Elitism = e;
Parameter = p;
}
//設置交叉率和變異率
void Genetic::SetProbability(double c, double m)
{
CrossProb = c;
MutProb = m;
}
//獲得第i個個體基因字串
const char* Genetic::GetGeneStr(int i)
{
return Individual[i].Chrom.GetGeneStr();
}
//計算所有個體適合度
void Genetic::AllFit()
{
for(int i=0; i<IndNumber; i++)
GetFit(i);
}
//個體適合度計算
double Genetic::GetFit(int i)
{
Individual[i].Fit = Individual[i].Val;
return Individual[i].Fit;
}
//計算所有個體評價函數值
void Genetic::AllVal()
{
for(int i=0; i<IndNumber; i++)
GetVal(i);
}
//計算個體評價函數值
double Genetic::GetVal(int i)
{
return EvalVal(Individual[i]);
}
//滾輪選擇方法
int Genetic::Wheel(double* index, int len)
{
double random = (rand()/(double)RAND_MAX)*index[len-1];
int i = 0;
while(random>index[i] && i<len-1) i++;
return i;
}
//雙親選擇方法
int Genetic::ParentSelect()
{
return Wheel(FitIndex,IndNumber);
}
//按適合度排序索引數組
void Genetic::IndexSort()
{
for(int i=0; i<IndNumber; i++)
{
int max = i;
for(int j=i; j<IndNumber; j++)
if(Individual[IndIndex[max]].Val<Individual[IndIndex[j]].Val)
max = j;
int t = IndIndex[max];
IndIndex[max] = IndIndex[i];
IndIndex[i] = t;
}
}
//算子選擇方法:0-交叉算子,1-變異算子
int Genetic::OperatorSelect()
{
return Wheel(OperatorFit,2);
}
//變異再生方法
void Genetic::GenMutation()
{
if(CurrentChild>=ChildrenNum) return;
int parent = ParentSelect();
Children[CurrentChild].Chrom = Individual[parent].Chrom.Mutation(MutProb);
CurrentChild++;
}
//交叉再生方法
void Genetic::GenCross()
{
if(CurrentChild>=ChildrenNum-1) return;
int parent1 = ParentSelect();
int parent2 = ParentSelect();
if((rand()/(double)RAND_MAX)<CrossProb)
{
if(Cross == ONE_POINT)
Individual[parent1].Chrom.OneCross(Individual[parent2].Chrom,
Children[CurrentChild].Chrom,
Children[CurrentChild+1].Chrom);
else if(Cross == TWO_POINT)
Individual[parent1].Chrom.TwoCross(Individual[parent2].Chrom,
Children[CurrentChild].Chrom,
Children[CurrentChild+1].Chrom);
else
Individual[parent1].Chrom.UniCross(Individual[parent2].Chrom,
Children[CurrentChild].Chrom,
Children[CurrentChild+1].Chrom);
}
else
{
Children[CurrentChild].Chrom = Individual[parent1].Chrom;
Children[CurrentChild+1].Chrom = Individual[parent2].Chrom;
}
CurrentChild += 2;
}
//精英方法
void Genetic::GenElitism()
{
int elitismNum = int(ChildrenNum*ElitismProb);
if(elitismNum <1) elitismNum = 1;
if(CurrentChild+elitismNum>IndNumber)
elitismNum = IndNumber-CurrentChild;
for(int i=CurrentChild; i<CurrentChild+elitismNum; i++)
Children[i].Chrom = Individual[IndIndex[i]].Chrom;
CurrentChild += elitismNum;
}
//產生新一代
void Genetic::Generation()
{
CurrentChild = 0;
if(Elitism==ELITISM) GenElitism();
while(CurrentChild < ChildrenNum-1)
{
if(OperatorSelect()==1 || CurrentChild>=ChildrenNum-1)
GenMutation();
else
GenCross();
}
INDIVIDUAL *tmpInd;
tmpInd = Individual;
Individual = Children;
Children = tmpInd;
// for(int i=0; i<ChildrenNum; i++)
// Individual[IndIndex[IndNumber-i-1]].Chrom = Children[i].Chrom;
Prepare();
}
//運行遺傳算法
const char* Genetic::Run(unsigned long gn)
{
Prepare();
double OperatorStep=0;
if(Parameter == GEN_INTERPOLATION)
OperatorStep = (OperatorEnd[0]-OperatorStart[0])/gn;
for(unsigned long generator=0; generator<gn; generator++)
{
if(Parameter == GEN_INTERPOLATION)
OperatorFit[0] += OperatorStep;
Generation();
if(Communication!=NULL)
Communication(Individual[IndIndex[0]].Chrom.GetGeneStr(),
Individual[IndIndex[0]].Fit,
Individual[IndIndex[0]].Val);
}
return Individual[IndIndex[0]].Chrom.GetGeneStr();
}
//準備遺傳運算
void Genetic::Prepare()
{
AllVal();
IndexSort();
AllFit();
CalFitIndex();
}
//設置初始算子適合度
void Genetic::SetOptStartEnd(double s1,double e1,double s2,double e2)
{
OperatorStart[0] = s1;
OperatorStart[1] = s2;
OperatorEnd[0] = e1;
OperatorEnd[1] = e2;
OperatorFit[0] = OperatorStart[0];
OperatorFit[1] = OperatorStart[0]+OperatorEnd[0];
}?? 快捷鍵說明
復制代碼
Ctrl + C
搜索代碼
Ctrl + F
全屏模式
F11
切換主題
Ctrl + Shift + D
顯示快捷鍵
?
增大字號
Ctrl + =
減小字號
Ctrl + -