Beispiel #1
0
int main(void)
{
    char choice;
    printf("Please press desired key to continue ... \n\n ");

    do
    {
        printf("\nMENU\n\n"
                " + : addition\n"
                " - : substraction\n "
                " * : multiplication\n "
                " / : division\n"
                " ^ : power\n"
                " q : quit\n\n");

        printf("Command: ");
        scanf(" %c ", &choice);

        switch(choice)
        {
            case '+': summation(); break;
            case '-': substraction(); break;
            case '*': multiplication(); break;
            case '/': division(); break;
            case '^': toThePower(); break;
            case 'q': break;

            default:
            {
                fprintf(stderr, "you didn't press expected key :(\n");
            }
         }
    }
    while (choice != 'q');
}
/********** Cr� la population **********/ 
void itsHybridContinuousInteractingAntColony::createAnts()
{

  // r�ervations vecteurs

  antProbaMemory.reserve( antsNb );
  //antMoveRange.reserve( antsNb*SpaceDim() );
  antMoveRange.reserve( antsNb );
  antCurrentPoint.reserve( antsNb * this->getProblem()->getDimension() );
  antCurrentValue.reserve( antsNb );
  // trop gourmand : antIncomingPoints.reserve( antsNb*antsNb*SpaceDim() );
  antIncomingPoints.reserve( antsNb*antsNb );
  antIncomingValues.reserve( antsNb*antsNb );
  antState.reserve( antsNb );
  
  for( unsigned int i=0; i < antsNb; i++ ) {
    
    // tirage al�toire uniforme sur l'hypercube de l'espace de recherche
    
    vector<double> aPoint;
    /*
    aPoint.reserve( this->getProblem()->getDimension() );
    aPoint = randomUniform( this->getProblem()->boundsMinima(), this->getProblem()->boundsMaxima() );
    */
    aPoint = this->getSamplePointAddr(i)->getSolution();
    
    // tire suivant N l'amplitude max de mouvement
    // distribution normale sur la moyenne de l'amplitude de l'espace de recherche
    double aMoveRange;
    aMoveRange = abs( randomNormal( 
				  mean( substraction(this->getProblem()->boundsMaxima(),this->getProblem()->boundsMinima()) ) * moveRangeMeanRatio, 
				  1/2 * mean( substraction(this->getProblem()->boundsMaxima(),this->getProblem()->boundsMinima()) ) * moveRangeStdRatio 
				  ) );
    
    // tire sur N la probabilit�de d�art d'utiliser un type de m�oire
    double aProbaUseMemory;
    aProbaUseMemory = randomNormal( probaUseMemoryMean, probaUseMemoryStd );
    // corrige les d�assements
    if ( aProbaUseMemory < 0 ) { aProbaUseMemory = 0; }
    if ( aProbaUseMemory > 1 ) { aProbaUseMemory = 1; }
    
    // ajoute la fourmi
    addAnt( aPoint, aMoveRange, aProbaUseMemory );
  }
}
/********** Evapore les sports **********/
void itsHybridContinuousInteractingAntColony::spotsEvaporate()
{
  // r�uit l'attrait des spots
  // S - (1-p) * S
  spotsValues = substraction( 
				   spotsValues,
				   multiply( spotsValues, (1-spotsPersistence ) )
				   );

  // supprime les spots trop faibles
  unsigned int i;
  for( i=0; i < spotsValues.size(); i++ ) {
    if( spotsValues[i] <= spotsMinValue ) {
      spotsValues.erase( spotsValues.begin()+i );
      spotsPoints.erase( spotsPoints.begin()+i );
    }
  }
}
void itsHybridEstimationOfDistribution::simplex()
{
  // if no given NMS evaluations number
  if( getSimplexEvaluations() == -1 ) {
    //setSimplexEvaluations( (int)floor( pow( (this->problem->getDimension() + 1 ), 2.0 ) ) );
    setSimplexEvaluations( this->getProblem()->getDimension() + 10 );
  }
  
  for( unsigned int i=0; i < getSampleSizeCurrent(); i++ ) {
    itsNelderMead nms;
  
    // problem optimized
    nms.setProblem( this->getProblem() );
  
    // no ending stopping criteria
    nms.setValueMin(0.0);
    nms.setIterationsMaxNumber( this->getIterationsMaxNumber() );
  
    // used stopping criterion
    nms.setEvaluationsMaxNumber( this->simplexEvaluations );
  
    // edges from sample hypercube
    vector<double> edges = 
      multiply(
        substraction(
          this->getProblem()->boundsMaxima(),
          this->getProblem()->boundsMinima()
        ),
        1 / ( pow( (double)getSampleSizeCurrent(), (double)1.0/this->getProblem()->getDimension() ) - 1 )
      );
      
    // init on current point
    nms.initSimplexFromBasePoint( getSamplePoint(i), edges );
  
    // silent launch
    nms.startSilent();
    
    // change the point to the new local optimum
    setSamplePoint( i, nms.getOptimum() );
  }
}
Beispiel #5
0
void menu(int m1, int n1, int m2, int n2, int m3, int n3)
{
    printf("\n1.Read an Array.\n2.Print an Array.\n3.Addition of 2 Arrays.\n4.Substraction of 2 Arrays.\n5.Multiplication of 2 Arrays.\n6.Multiplication of an Array by a Number.\n7.Transpose of a Matrix.\n8.Determinant of a Matrix.\n9.Exit.\n");
    scanf("%d",&f);
    switch (f) {
        case 1:
            read(x, &m1, &n1, y, &m2, &n2, z, &m3, &n3);
            menu(m1, n1, m2, n2, m3, n3);
            break;
            
        case 2:
            printa(x, m1, n1, y, m2, n2, z, m3, n3);
            printf("\n1.Menu.\n2.Exit.\n");
            scanf("%d",&f);
            switch (f) {
                case 1:
                    menu(m1, n1, m2, n2, m3, n3);
                    break;
                case 2:
                    break;
                
                default:
                    break;
            }
            
            break;
            
        case 3:
            Addition(x, m1, n1, y, m2, n2, z, m3, n3, &m1, &n1, &m2, &n2, &m3, &n3);
            menu(m1, n1, m2, n2, m3, n3);
            break;
            
        case 4:
            substraction(x, m1, n1, y, m2, n2, z, m3, n3, &m1, &n1, &m2, &n2, &m3, &n3);
            menu(m1, n1, m2, n2, m3, n3);
            break;
            
        case 5:
            multiplication_array(x, m1, n1, y, m2, n2, z, m3, n3, &m1, &n1, &m2, &n2, &m3, &n3);
            menu(m1, n1, m2, n2, m3, n3);
            break;
        
        case 6:
            multiplaction_number(x, m1, n1, y, m2, n2, z, m3, n3, &m1, &n1, &m2, &n2, &m3, &n3);
            menu(m1, n1, m2, n2, m3, n3);
            break;
        
        case 7:
            transpose(x, m1, n1, y, m2, n2, z, m3, n3, &m1, &n1, &m2, &n2, &m3, &n3);
            menu(m1, n1, m2, n2, m3, n3);
            break;
            
        case 8:
            determinant(x, m1, n1, y, m2, n2, z, m3, n3, &m1, &n1, &m2, &n2, &m3, &n3);
            menu(m1, n1, m2, n2, m3, n3);
            break;
            
        case 9:
            break;
            
        default:
            break;
    }
}