gayhdlg.cpp

这是个关于基于遗传算法的Schaffer F6函数优化的程序代码。

// GAyhDlg.cpp : implementation file
//

#include "stdafx.h"
#include "GAyh.h"
#include "GAyhDlg.h"
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <time.h>

#ifdef _DEBUG
#define new DEBUG_NEW
#undef THIS_FILE
static char THIS_FILE[] = __FILE__;
#endif

/////////////////////////////////////////////////////////////////////////////
// CAboutDlg dialog used for App About

class CAboutDlg : public CDialog
{
public:
	CAboutDlg();

// Dialog Data
	//{{AFX_DATA(CAboutDlg)
	enum { IDD = IDD_ABOUTBOX };
	//}}AFX_DATA

	// ClassWizard generated virtual function overrides
	//{{AFX_VIRTUAL(CAboutDlg)
	protected:
	virtual void DoDataExchange(CDataExchange* pDX);    // DDX/DDV support
	//}}AFX_VIRTUAL

// Implementation
protected:
	//{{AFX_MSG(CAboutDlg)
	//}}AFX_MSG
	DECLARE_MESSAGE_MAP()
};

CAboutDlg::CAboutDlg() : CDialog(CAboutDlg::IDD)
{
	//{{AFX_DATA_INIT(CAboutDlg)
	//}}AFX_DATA_INIT
}

void CAboutDlg::DoDataExchange(CDataExchange* pDX)
{
	CDialog::DoDataExchange(pDX);
	//{{AFX_DATA_MAP(CAboutDlg)
	//}}AFX_DATA_MAP
}

BEGIN_MESSAGE_MAP(CAboutDlg, CDialog)
	//{{AFX_MSG_MAP(CAboutDlg)
		// No message handlers
	//}}AFX_MSG_MAP
END_MESSAGE_MAP()

/////////////////////////////////////////////////////////////////////////////
// CGAyhDlg dialog

CGAyhDlg::CGAyhDlg(CWnd* pParent /*=NULL*/)
	: CDialog(CGAyhDlg::IDD, pParent)
{
	//{{AFX_DATA_INIT(CGAyhDlg)
	m_pc = 0.6;
	m_pm = 0.1;
	m_maxgeneration = 500;
	m_size =100;
	m_fxy = 0.0;
	m_x = 0.0;
	m_y = 0.0;
	//}}AFX_DATA_INIT
	// Note that LoadIcon does not require a subsequent DestroyIcon in Win32
	m_hIcon = AfxGetApp()->LoadIcon(IDR_MAINFRAME);
}

void CGAyhDlg::DoDataExchange(CDataExchange* pDX)
{
	CDialog::DoDataExchange(pDX);
	//{{AFX_DATA_MAP(CGAyhDlg)
	DDX_Control(pDX, IDC_LIST_SHOW, m_show);
	DDX_Text(pDX, IDC_PC, m_pc);
	DDX_Text(pDX, IDC_pm, m_pm);
	DDX_Text(pDX, IDC_MAXGENERATION, m_maxgeneration);
	DDX_Text(pDX, IDC_POPSIZE, m_size);
	DDX_Text(pDX, IDC_EDIT1, m_fxy);
	DDX_Text(pDX, IDC_EDIT2, m_x);
	DDX_Text(pDX, IDC_EDIT3, m_y);
	//}}AFX_DATA_MAP
}

BEGIN_MESSAGE_MAP(CGAyhDlg, CDialog)
	//{{AFX_MSG_MAP(CGAyhDlg)
	ON_WM_SYSCOMMAND()
	ON_WM_PAINT()
	ON_WM_QUERYDRAGICON()
	ON_BN_CLICKED(IDC_YHRUN, OnYhrun)
	//}}AFX_MSG_MAP
END_MESSAGE_MAP()

/////////////////////////////////////////////////////////////////////////////
// CGAyhDlg message handlers

BOOL CGAyhDlg::OnInitDialog()
{
	CDialog::OnInitDialog();

	// Add "About..." menu item to system menu.

	// IDM_ABOUTBOX must be in the system command range.
	ASSERT((IDM_ABOUTBOX & 0xFFF0) == IDM_ABOUTBOX);
	ASSERT(IDM_ABOUTBOX < 0xF000);

	CMenu* pSysMenu = GetSystemMenu(FALSE);
	if (pSysMenu != NULL)
	{
		CString strAboutMenu;
		strAboutMenu.LoadString(IDS_ABOUTBOX);
		if (!strAboutMenu.IsEmpty())
		{
			pSysMenu->AppendMenu(MF_SEPARATOR);
			pSysMenu->AppendMenu(MF_STRING, IDM_ABOUTBOX, strAboutMenu);
		}
	}

	// Set the icon for this dialog.  The framework does this automatically
	//  when the application's main window is not a dialog
	SetIcon(m_hIcon, TRUE);			// Set big icon
	SetIcon(m_hIcon, FALSE);		// Set small icon
	
	// TODO: Add extra initialization here
    CRect rect;
	m_show.GetClientRect(&rect);
	int width=rect.Width()/4;
	m_show.InsertColumn(0,_T("遗传代数"),LVCFMT_LEFT,width*0.8);
	m_show.InsertColumn(1,_T("平均适应度"),LVCFMT_LEFT,width*0.8);
	m_show.InsertColumn(2,_T("最优值"),LVCFMT_LEFT,width*0.8);
	m_show.InsertColumn(4,_T("x值"),LVCFMT_LEFT,width*0.8);
    m_show.InsertColumn(5,_T("y值"),LVCFMT_LEFT,width);
	InsertItems();
	return TRUE;  // return TRUE  unless you set the focus to a control
}

void CGAyhDlg::OnSysCommand(UINT nID, LPARAM lParam)
{
	if ((nID & 0xFFF0) == IDM_ABOUTBOX)
	{
		CAboutDlg dlgAbout;
		dlgAbout.DoModal();
	}
	else
	{
		CDialog::OnSysCommand(nID, lParam);
	}
}

// If you add a minimize button to your dialog, you will need the code below
//  to draw the icon.  For MFC applications using the document/view model,
//  this is automatically done for you by the framework.

void CGAyhDlg::OnPaint() 
{
	if (IsIconic())
	{
		CPaintDC dc(this); // device context for painting

		SendMessage(WM_ICONERASEBKGND, (WPARAM) dc.GetSafeHdc(), 0);

		// Center icon in client rectangle
		int cxIcon = GetSystemMetrics(SM_CXICON);
		int cyIcon = GetSystemMetrics(SM_CYICON);
		CRect rect;
		GetClientRect(&rect);
		int x = (rect.Width() - cxIcon + 1) / 2;
		int y = (rect.Height() - cyIcon + 1) / 2;

		// Draw the icon
		dc.DrawIcon(x, y, m_hIcon);
	}
	else
	{
		CDialog::OnPaint();
	}
}

// The system calls this to obtain the cursor to display while the user drags
//  the minimized window.
HCURSOR CGAyhDlg::OnQueryDragIcon()
{
	return (HCURSOR) m_hIcon;
}

genotype* CGAyhDlg::newsize()
{
	genotype *p;
	p=new genotype[m_size+1];
	return p;
}


void CGAyhDlg::OnYhrun() 
{
	// TODO: Add your control notification handler code here
UpdateData(TRUE);
srand((unsigned)time(NULL));
generation = 0;
initialize();
evaluate();
keep_the_best();
while(generation<m_maxgeneration)
      {
      generation++;
      select();
      across();
      mutate();
      report();
      evaluate();
      elitist();
      }
	InsertItems();
	m_show.SetRedraw(TRUE);
	m_fxy=population[m_size].fitness;
	m_x=population[m_size].gene[0];
	m_y=population[m_size].gene[1];
	UpdateData(FALSE);
	delete population;
	delete newpopulation;
}

void CGAyhDlg::initialize()
{
int i, j;
double lbound=-10.0;
double ubound=10.0;
population=newsize();
newpopulation=newsize();
data=new Data[m_maxgeneration];
for (i = 0; i < NVARS; i++)
      {
      for (j = 0; j < m_size; j++)
           {
           population[j].fitness = 0;
           population[j].rfitness = 0;
           population[j].cfitness = 0;
           population[j].lower[i] = lbound;
           population[j].upper[i]= ubound;
           population[j].gene[i] = randval(population[j].lower[i],
                                   population[j].upper[i]);
           }
      }
}

double CGAyhDlg::randval(double low, double high)
{
  double val;
  val = ((double)(rand()%1000)/1000.0)*(high - low) + low;
  return(val);
}

void CGAyhDlg::evaluate()
{
	int mem;
int i;
double x[NVARS+1];

for (mem = 0; mem < m_size; mem++)
      {
      for (i = 0; i < NVARS; i++)
            x[i+1] = population[mem].gene[i];
      
      population[mem].fitness = 0.5-(sin(sqrt((x[1]-2)*(x[1]-2)+x[2]*x[2]))*sin(sqrt((x[1]-2)*(x[1]-2)+x[2]*x[2]))-0.5)/((1+0.001*((x[1]-2)*(x[1]-2)+x[2]*x[2]))*(1+0.001*((x[1]-2)*(x[1]-2)+x[2]*x[2])));
      }
}

void CGAyhDlg::keep_the_best()
{
  int mem;
int i;
cur_best = 0; /* stores the index of the best individual */

for (mem = 0; mem < m_size; mem++)
      {
      if (population[mem].fitness > population[m_size].fitness)
            {
            cur_best = mem;
            population[m_size].fitness = population[mem].fitness;
            }
      }
/* once the best member in the population is found, copy the genes */
for (i = 0; i < NVARS; i++)
      population[m_size].gene[i] = population[cur_best].gene[i];
}

void CGAyhDlg::elitist()
{
  int i;
double best, worst;             /* best and worst fitness values */
int best_mem, worst_mem; /* indexes of the best and worst member */

best = population[0].fitness;
worst = population[0].fitness;
for (i = 0; i < m_size - 1; ++i)
      {
      if(population[i].fitness > population[i+1].fitness)
            {      
            if (population[i].fitness >= best)
                  {
                  best = population[i].fitness;
                  best_mem = i;
                  }
            if (population[i+1].fitness <= worst)
                  {
                  worst = population[i+1].fitness;
                  worst_mem = i + 1;
                  }
            }
      else
            {
            if (population[i].fitness <= worst)
                  {
                  worst = population[i].fitness;
                  worst_mem = i;
                  }
            if (population[i+1].fitness >= best)
                  {
                  best = population[i+1].fitness;
                  best_mem = i + 1;
                  }
            }
      }

if (best >= population[m_size].fitness)
    {
    for (i = 0; i < NVARS; i++)
       population[m_size].gene[i] = population[best_mem].gene[i];
    population[m_size].fitness = population[best_mem].fitness;
    }
else
    {
    for (i = 0; i < NVARS; i++)
       population[worst_mem].gene[i] = population[m_size].gene[i];
    population[worst_mem].fitness = population[m_size].fitness;
    } 
}

void CGAyhDlg::select()
{
	int mem, i, j;
double sum = 0;
double p;

/* find total fitness of the population */
for (mem = 0; mem < m_size; mem++)
      {
      sum += population[mem].fitness;
      }

/* calculate relative fitness */
for (mem = 0; mem < m_size; mem++)
      {
      population[mem].rfitness =  population[mem].fitness/sum;
      }
population[0].cfitness = population[0].rfitness;

/* calculate cumulative fitness */
for (mem = 1; mem < m_size; mem++)
      {
      population[mem].cfitness =  population[mem-1].cfitness +       
                          population[mem].rfitness;
      }

/* finally select survivors using cumulative fitness. */

for (i = 0; i < m_size; i++)
      { 
      p = rand()%1000/1000.0;
      if (p < population[0].cfitness)
            newpopulation[i] = population[0];      
      else
            {
            for (j = 0; j < m_size;j++)      
                  if (p >= population[j].cfitness && 
                              p<population[j+1].cfitness)
                        newpopulation[i] = population[j+1];
            }
      }
/* once a new population is created, copy it back */

for (i = 0; i < m_size; i++)
      population[i] = newpopulation[i];      

}

void CGAyhDlg::across()
{
  int mem, one;
int first  =  0; /* count of the number of members chosen */
double x;

for (mem = 0; mem < m_size; ++mem)
      {
      x = rand()%1000/1000.0;
      if (x < m_pc)
            {
            ++first;
            if (first % 2 == 0)
                  Xover(one, mem);
            else
                  one = mem;
            }
      }
}

void CGAyhDlg::Xover(int one, int two)
{
  int i;
int point; /* crossover point */

/* select crossover point */
if(NVARS > 1)
   {
   if(NVARS == 2)
         point = 1;
   else
         point = (rand() % (NVARS - 1)) + 1;

   for (i = 0; i < point; i++)
        swap(&population[one].gene[i], &population[two].gene[i]);

   }
}

void CGAyhDlg::swap(double *x, double *y)
{
  double temp;

temp = *x;
*x = *y;
*y = temp;
}

void CGAyhDlg::mutate()
{
  int i, j;
double lbound, hbound;
double x;

for (i = 0; i < m_size; i++)
      for (j = 0; j < NVARS; j++)
            {
            x = rand()%1000/1000.0;
            if (x < m_pm)
                  {
                  /* find the bounds on the variable to be mutated */
                  lbound = population[i].lower[j];
                  hbound = population[i].upper[j];  
                  population[i].gene[j] = randval(lbound, hbound);
                  }
            }
}

void CGAyhDlg::report()
{
  int i;
double best_val;            /* best population fitness */
double avg;                 /* avg population fitness */
double stddev;              /* std. deviation of population fitness */
double sum_square;          /* sum of square for std. calc */
double square_sum;          /* square of sum for std. calc */
double sum;                 /* total population fitness */

sum = 0.0;
sum_square = 0.0;

for (i = 0; i < m_size; i++)
      {
      sum += population[i].fitness;
      sum_square += population[i].fitness * population[i].fitness;
      }

avg = sum/(double)m_size;
square_sum = avg * avg * m_size;
stddev = sqrt((sum_square - square_sum)/(m_size - 1));
best_val = population[m_size].fitness;
data[generation-1].avefitness=avg;
data[generation-1].bestvalue=best_val;
data[generation-1].xbest=population[m_size].gene[0];
data[generation-1].ybest=population[m_size].gene[1];
}

void CGAyhDlg::InsertItems()
{
  	m_show.DeleteAllItems();
	int i;
	LVITEM lvi;
	CString strItem;
	
	for(i=1;i<=generation;i++)
	{
		lvi.mask =  LVIF_TEXT;
		lvi.iItem = i-1;

		strItem.Format(_T("%d"), i);
		lvi.iSubItem =0;
		lvi.pszText = (LPTSTR)(LPCTSTR)(strItem);
		m_show.InsertItem(&lvi);

		strItem.Format(_T("%f"), data[i-1].avefitness);
		lvi.iSubItem =1;
		lvi.pszText = (LPTSTR)(LPCTSTR)(strItem);
		m_show.SetItem(&lvi);

		strItem.Format(_T("%f"),data[i-1].bestvalue);
		lvi.iSubItem =2;
		lvi.pszText = (LPTSTR)(LPCTSTR)(strItem);
		m_show.SetItem(&lvi);

		strItem.Format(_T("%f"), data[i-1].xbest);
		lvi.iSubItem =3;
		lvi.pszText = (LPTSTR)(LPCTSTR)(strItem);
		m_show.SetItem(&lvi);

	strItem.Format(_T("%f"), data[i-1].ybest);
		lvi.iSubItem =4;
		lvi.pszText = (LPTSTR)(LPCTSTR)(strItem);
		m_show.SetItem(&lvi);

	}
}