cgroup.cs

C#编写的遗传算法程序

using System;
/// <summary>
/// Group 的摘要说明。
/// </summary>
public class CGroup
{
	

	// Construction

	// Attributes
	//public:
	/*            The Dfinition of Constant         */
	/*            The Dfinition of Constant         */
	static int POPSIZE=501; //POPULATION SIZE
	static int MAXIMIZATION=1; //maximization flag
	static int MINIMIZATION=2; //minimization flag
	static int SN=1024;

	static int FunctionMode=MAXIMIZATION;
	/*			The Definition of User Data
			(For different problem, there are some difference.) */

	static int Cmax=100	;	//certain maximal value
	static int Cmin=0;		//certain minimum valuePOPSIZE 501 //POPULATION SIZE



	//static double PI=3.1415926 ;
	static double PI=Math.PI ;

	/*			The Definition of User Data
			(For different problem, there are some difference.) */



	public double[] gef=new double[SN],gex=new double[SN];
	private System.Random random;
	public int PopSize, Pointnum,i,j;			//population size
	public int MaxGeneration;	//max. numberof generation
	public double Pc;			//probability of crossover
	public double Pm;		//probability of mutation
	double averagevalue,fangcha;
	public double outa,outb,outsita,outfai;
	int generation;			//number of generation
	int best_index;			//index of best individual
	int worst_index;			//index of worst individual
	class individual		//data structure of individual
	{
		public char[] chrom=new char[61];//A STRING OF CODE REPRESENTING INDIVIDUAL
		public double value;		//object value of this individual
		public double fitness;	//fitness value of this individual
		public bool dirty;
	};
	individual bestindividual=new individual();//best indidual of current generation
	individual worstindividual=new individual();//worst individual of current generation
	individual currentbest=new individual();    //best individual by nowstruct individual population[POPSIZE];//population
	individual[] population=new individual[POPSIZE];

	int LENGTH1, LENGTH2, LENGTH3, LENGTH4, CHROMLENGTH;



	public CGroup()
	{
		generation=0;
		averagevalue=0.0;
		Pointnum=1024;
		PopSize=80;
		MaxGeneration=200;
		Pc=0.6;
		Pm=0.01;
		random=new System .Random ();
		LENGTH1=(int)Math.Ceiling(Math.Log(Pointnum)/Math.Log(2));		//*the chromosome length of 1st variable
		LENGTH2=(int)Math.Ceiling(Math.Log(Pointnum)/Math.Log(2));	//*the chromosome length of 2nd variable
		LENGTH3=(int)Math.Ceiling(Math.Log(Pointnum)/Math.Log(2));		//*the chromosome length of 3nd variable
		LENGTH4=(int)Math.Ceiling(Math.Log(Pointnum)/Math.Log(2));		//*the chromosome length of 4nd variable
		CHROMLENGTH=LENGTH1+LENGTH2+LENGTH3+LENGTH4;	//total length of chromosome
		for(int i=0;i<CHROMLENGTH;i++)
			bestindividual.chrom[i]='0';
		bestindividual.chrom[CHROMLENGTH]='\0';
		bestindividual.fitness=0.0;
		bestindividual.value=0.0;
		for(i=0;i<CHROMLENGTH;i++)
			currentbest.chrom[i]='0';
		currentbest.chrom[CHROMLENGTH]='\0';
		currentbest.fitness=0.0;
		currentbest.value=0.0;
		for(i=0;i<Pointnum;i++)
			gex[i]=i*1.0/Pointnum;
	}



	public void GenerateInitialPopulation()
	{
		int i,j;float iii;
		generation=0;
		averagevalue=0;
		for(i=0;i<POPSIZE;i++)
			population[i]=new individual();
		for(i=0;i<CHROMLENGTH;i++)
			bestindividual.chrom[i]='0';
		bestindividual.chrom[CHROMLENGTH]='\0';
		bestindividual.fitness=0.0;
		bestindividual.value=0.0;

		for(i=0;i<CHROMLENGTH;i++)
			currentbest.chrom[i]='0';
		currentbest.chrom[CHROMLENGTH]='\0';
		currentbest.fitness=0.0;
		currentbest.value=0.0;

		for(i=0;i<PopSize;i++)
		{
			for(j=0;j<CHROMLENGTH;j++)
			{
				iii=(float)Rand(10.0);
				population[i].chrom[j]=(iii<5.0)?'0':'1';
			}
			population[i].chrom[CHROMLENGTH]='\0';
			population[i].dirty=true;
		}
		EvaluatePopulation();
	}

	/*				Function:Initialize the first generation.
							Variable:None.                 */
	public void GenerateNextPopulation()
	{
		generation++;
		SelectionOperator();
		CrossoverOperator();
		MutationOperator();
		EvaluatePopulation();
		PerformEvolution();
	}

	/*				Function:Evaluate population accordingto certain formula.
							Variable:None.                  */
	void EvaluatePopulation()
	{
		CalculateObjectValue();			//calculate object value
		CalculateFitnessValue();		//calculate finess value
		Annealing();
		FindBestAndWorstIndividual();	//find the best and worst individual
	}

	/*				Function:To decode a binary chromosome into a decimal integer.
							Variable:None.
					Note:The returned value may be plus,or minus.
							For fifferent coding method,this value may be changed into
							"unsigned int".                                         */
	int DecodeChromosome(char[] String,int point,int length)
	{
		int i;
		int Decimal=0;
		char[] pointer=new char[20];
		System.Array.Copy(String,point,pointer,0,length);  //pointer=string+point;

		for(i=1;i<length;i++)
			pointer[i]=(pointer[i-1]==pointer[i])?'0':'1';
		for(i=0;i<length;i++)
		{
			Decimal+=(pointer[i]-'0')*(int)Math.Pow(2,length-1-i);
		}
		return(Decimal);
	}

	public void DecodeBest()
	{
		int temp1,temp2,temp3,temp4;
		temp1=DecodeChromosome(currentbest.chrom,0,LENGTH1);
		temp2=DecodeChromosome(currentbest.chrom,LENGTH1,LENGTH2);
		temp3=DecodeChromosome(currentbest.chrom,LENGTH1+LENGTH2,LENGTH3);
		temp4=DecodeChromosome(currentbest.chrom,LENGTH1+LENGTH2+LENGTH3,LENGTH4);
		if(temp1==0)temp2=0;
		outa=temp1/20.0;
		outb=temp2/(double)Pointnum;
		outsita=temp3/20.0;
		outfai=2*PI*temp4/Pointnum;
	}
	/*				Function:To calculate object value.
							Variable:None.
						Note:For different problem, user must change these code.This
								example is dealing with Rosenbrock function. Rosenbrock 
								function is defined as:f(x1,x2)=100*(x1**2-x2)**2+(1-x1)**2
								Its maxmal value is:f(-2.048,-2.048)=3905.926227       */
	void CalculateObjectValue()
	{
		int i;
		int temp3,temp4,temp1,temp2;
		double x1,x2,x3,x4;
		//Rosenbrock function
		for(i=0;i<PopSize;i++)
		{
			if(population[i].dirty)
			{
				temp1=DecodeChromosome(population[i].chrom,0,LENGTH1);
				temp2=DecodeChromosome(population[i].chrom,LENGTH1,LENGTH2);
				temp3=DecodeChromosome(population[i].chrom,LENGTH1+LENGTH2,LENGTH3);
				temp4=DecodeChromosome(population[i].chrom,LENGTH1+LENGTH2+LENGTH3,LENGTH4);
				if(temp1==0)
					temp2=0;
				x1=temp1/20.0;
				x2=temp2/(double)Pointnum;						
				x3=temp3/20.0;
				x4=2*PI*temp4/Pointnum;
				CalPopulation(i,x1,x2,x3,x4);	
			}
		}
	}
	void CalPopulation(int i,double x1,double x2,double x3,double x4)
	{
		double sum;
		int jj;
		double k;
		if(true)
		{
			sum=0.0;
			for(jj=0;jj<Pointnum;jj++)
			{
				sum=sum+Math.Pow(impulse(gex[jj],x1,x2,x3,x4),2.0);
			}
			k=1.0/Math.Sqrt(sum);
			population[i].value=0.0;
			for(jj=0;jj<Pointnum;jj++)
			{						
				population[i].value+=gef[jj]*k*impulse(gex[jj],x1,x2,x3,x4);
				
			}
		}
		else
		{
			
			sum=0.0;
			for(j=0;j<Pointnum;++j)
			{
				sum += Math.Pow(gef[j] - impulse(gex[j],x1,x2,x3,x4),2);				
			}
			k = 1.0 / ( Math.Sqrt(sum * Pointnum));
			population[i].value=0.0;
			for(jj=0;jj<128;jj++)
			{						
				if(Math.Abs(gef[jj]) > Double.Epsilon)
					population[i].value+=k*impulse(gex[jj],x1,x2,x3,x4)/gef[jj];							
			}
		}
	}
	/*				fUNCTION:TO CALCULATE FITNESS VALUE.
							Variable:None.							*/
	void CalculateFitnessValue()
	{
		int i;
		double temp=0.0;

		for(i=0;i<PopSize;i++)
		{
			if(population[i].dirty==true)
			{
				if(FunctionMode==MAXIMIZATION)
				{	//maximization
					temp=(Cmin+population[i].value)*(Cmin+population[i].value);
					//	temp=18000+population[i].value;
					//	ASSERT(temp>0);
				}
				else if(FunctionMode==MINIMIZATION)
				{	//minimization
					if(population[i].value<Cmax)
					{
						//AfxMessageBox("Error!!");
						temp=Cmax-population[i].value;}
					else
					{
						temp=0.0;
					}   
				}
				population[i].fitness=temp;
			}		
		}
	}

	/*                Function:To Find out the best individual so far current generation.
								Variable:None.                                                 */
	void FindBestAndWorstIndividual()
	{
		int i;
		//find out the best and worst individual of this generation
		getIndividual(bestindividual,population[0]);
		getIndividual(worstindividual,population[0]);
		best_index=worst_index=0;