main.cc

贝叶斯优化算法是一种新的演化算法

// ################################################################################
//
// name:          main.cc      
//
// author:        Martin Pelikan
//
// purpose:       main routine and the definition of input parameters
//
// last modified: February 1999
//
// ################################################################################

#include <stdio.h>

#include "boa.h"
#include "getFileArgs.h"
#include "args.h"
#include "fitness.h"
#include "startUp.h"
#include "header.h"

BoaParams boaParams;

// ==========================================================================
// the definition of input parameters that can be specified in the input file 

ParamStruct params[] =
{
  {PARAM_LONG,"populationSize",&boaParams.N,"1200","Size of the population",NULL},
  {PARAM_FLOAT,"parentsPercentage",&boaParams.percentParents,"50","The number of parents to select (% from population)",NULL},
  {PARAM_FLOAT,"offspringPercentage",&boaParams.percentOffspring,"50","Size of offspring to create (% from population)",NULL},

  {PARAM_DIVIDER,NULL,NULL,NULL,NULL,NULL},  

  {PARAM_INT,"fitnessFunction",&boaParams.fitnessNumber,"2","Number of fitness function to use",&getFitnessDesc},
  {PARAM_INT,"problemSize",&boaParams.n,"30","Size of the problem (of one dimension)",NULL},

  {PARAM_DIVIDER,NULL,NULL,NULL,NULL,NULL},  

  {PARAM_LONG,"maxNumberOfGenerations",&boaParams.maxGenerations,"200","Maximal Number of Generations to Perform",NULL},
  {PARAM_LONG,"maxFitnessCalls",&boaParams.maxFitnessCalls,"-1","Maximal Number of Fitness Calls (-1 when unbounded)",NULL},
  {PARAM_FLOAT,"epsilon",&boaParams.epsilon,"0.01","Termination threshold for the univ. freq. (-1 is ignore)",NULL},
  {PARAM_CHAR,"stopWhenFoundOptimum",&boaParams.stopWhenFoundOptimum,"0","Stop if the optimum was found?", &yesNoDescriptor},
  {PARAM_FLOAT,"maxOptimal",&boaParams.maxOptimal,"-1","Percentage of opt. & nonopt. ind. threshold (-1 is ignore)",NULL},
 
  {PARAM_DIVIDER,NULL,NULL,NULL,NULL,NULL},  

  {PARAM_INT,"maxIncoming",&boaParams.maxIncoming,"2","Maximal number of incoming edges in dep. graph for the BOA",NULL},

  {PARAM_DIVIDER,NULL,NULL,NULL,NULL,NULL},

  {PARAM_CHAR,"pause",&boaParams.pause,"0","Wait for enter after printing out generation statistics?",NULL},

  {PARAM_DIVIDER,NULL,NULL,NULL,NULL,NULL},

  {PARAM_STRING,"outputFile",&(boaParams.outputFilename),NULL,"Output file name",NULL},
  {PARAM_FLOAT,"guidanceThreshold",&boaParams.guidanceThreshold,"0.3","Threshold for guidance (closeness to 0,1)",NULL},

  {PARAM_DIVIDER,NULL,NULL,NULL,NULL,NULL},

  {PARAM_LONG,"randSeed",&boaParams.randSeed,"time","Random Seed",NULL},
  
  {PARAM_END,NULL,NULL,NULL,NULL}
};

// ================================================================================
//
// name:          main
//
// function:      calls the initialization, the BOA, and the done methods, simply
//                the main function
//
// parameters:    argc.........the number of arguments sent to the program
//                argv.........an array of arguments sent to the program (including
//                             its name and the path)
//
// returns:       (int) 0
//
// ================================================================================

int main(int argc, char **argv)
{
  // process the arguments, read the input file (if specified)

  startUp(argc, argv, params);

  // initialize the BOA

  initialize(&boaParams);

  // print the header to stdout, and most of the output files

  printTheHeader(stdout);
  printTheHeader(getLogFile());
  printTheHeader(getModelFile());

  // print the values of the parameters to stdout and the log file

  printParamValues(stdout,params);
  printParamValues(getLogFile(),params);

  // run the boa

  boa(&boaParams);

  // free the used resources

  done(&boaParams);

  // get back

  return 0;
};