mimic_onemax.cxx

改算法基于遗传算法

//                         Time-stamp: <2007-07-16 13:15:31 handa>
//
#include "stdafx.h"

#include <vector>
#include "chromoso.h"
#include <iostream>
#include "basic_edas.hxx"
#include "generatingRules.hxx"
#include "m2n.hxx"
#include "MIMIC.hxx"

using namespace std;

int main1(int argc, char **argv)
{
  int i,k,j;


  long   tcr = 100000; // terminal criterion for quitting experiment.
  int    ps  = 100000;   // population size for H-GA
  int    pools  = 200;   // pool size for H-GA
  int    sdg = 0;     // random seed for ga.
  int    sdp = 0;     // random seed for problem generation.
  char *fname;
  char *fnameout;
  int nod;
  int len = 20;

  if (argc != 7) {
    cerr << "Error is occurred!" << endl 
	 << "Usage: " << argv[0] << " seed seed factorcount linecount filein fileout" << endl;
    return 0;
  }
  sdp   = atoi(argv[1]);
  sdg   = atoi(argv[2]);
  len   = atoi(argv[3]);
  nod   = atoi(argv[4]);
  fname = argv[5];
  fnameout = argv[6];


  random_number rn(sdp), rn1(sdg);
  generatingRules<int> om(rn, len, nod, fname);

  list<chromosome<int> *> ch;
  vector<chromosome<int> *> pool(pools);
  for(i =0;i < ps;i++) {
    chromosome<int>* te = new chromosome<int>(om, i%nod);
    ch.push_back(te);
  }
  m2n<int> sel(rn1);

  mimic<int> eas(rn1, len, 3, 200, om);

  basic_EDAs<int> test(ch, eas, sel, om, pool);

    list<chromoIntP>::iterator il;

    double ave = 0.0;
    double max = 0.0;
    for (il = ch.begin(); il !=  ch.end(); il++) {
      ave += (*il)->fitness(0);
      if(max < (*il)->fitness(0)) max = (*il)->fitness(0);
    }
    cout <<ch.size()  <<  " ave: " << ave / ch.size() << "\tmax: " << max ;
    ave = 0.0;
    max = 0.0;
    // for (i = 0; i < 500; i++) { Wolf 2007/10/17
    for (i = 0; i < nod; i++) {
      double dtmp = om.maxFitInMatchingSet(ch, i);
      ave += dtmp;
      if(max < dtmp) max = dtmp;
    }
    
	// cout << " aveD: " << ave / 500 << "\tmaxD: " << max  << endl; Wolf 2007/10/17
     cout << " aveD: " << ave / nod << "\tmaxD: " << max  << endl;

  for(long t =0;t < 10;t++) {
    test.generation();
    cout << t << " th generation\n";
    ave = 0.0;
    max = 0.0;
    for (il = ch.begin(); il !=  ch.end(); il++) {
      ave += (*il)->fitness(0);
      if(max < (*il)->fitness(0)) max = (*il)->fitness(0);
    }
    cout <<ch.size()  <<  " ave: " << ave / ch.size() << "\tmax: " << max ;
    ave = 0.0;
    max = 0.0;
    // for (i = 0; i < 500; i++) { Wolf 2007/10/17
    for (i = 0; i < nod; i++) {
      double dtmp = om.maxFitInMatchingSet(ch, i);
      ave += dtmp;
      if(max < dtmp) max = dtmp;
    }
    // cout << " aveD: " << ave / 500 << "\tmaxD: " << max  << endl; Wolf 2007/10/17
    cout << " aveD: " << ave / nod << "\tmaxD: " << max  << endl;

  }
  FILE *fp = fopen(fnameout, "w");
  for (il = ch.begin(); il !=  ch.end(); il++) {
    if ((*il)->fitness(0) < 1.0005) continue; 
    for (i = 0; i < (*il)->Size(); i++) {
      fprintf(fp, "%d ", (*il)->getgene(i));
    }
    fprintf(fp, "%d ", (*il)->isDecedent());
    fprintf(fp, "%lf\n", (*il)->fitness(0));
  }
  fclose(fp);
}