/***************************************************************/* Single & Multi-Objective Real-Coded Genetic Algorithms Code *//* Author: Kumara Sastry                                       *//* Illinois Genetic Algorithms Laboratory (IlliGAL)            *//* Deparment of General Engineering                            *//* University of Illinois at Urbana-Champaign                  *//* 104 S. Mathews Ave, Urbana, IL 61801                        *//***************************************************************/#ifndef _POPULATION_H#define _POPULATION_Hclass GA;                 // Predeclaration for making friendsclass Selection;class Crossover;class Population;#include <assert.h>#include <iostream>#include <math.h>#include <fstream>#include "random.hpp"#include "globalSetup.hpp"#include "individual.hpp"#include "selection.hpp"#include "crossover.hpp"#include "localsearch.hpp"extern GlobalSetup *globalSetup;extern Random myRandom;class Population{protected:  Individual **guys;              // The chromosomes  Individual **newGuys;           // Individuals after crossover and mutation  int        *mpool;              // mating pool  Individual *bestInd;            // individual in the population    Selection *selection;           // Pointer to selection function  Crossover *crossover;           // Pointer to xover function  LocalSearch *localSearch;  int *freezeMask;    int	     noOfFeasible;  	  // number of feasible individuals
  double     *bestobj;              // maximum objective  double     *worstobj;              // minimum objective  double     *avgobj;              // average objective      double     *maxfit;              // maximum fitness  double     *minfit;              // minimum fitness  double     *avgfit;              // average fitness      double     *varfit;  double     *bestFitChange;  double     *avgFitChange;  double     *fitVarChange;  double     *bestObjChange;  double     *avgObjChange; public:    // Big 3  Population();  virtual ~Population();  // Declaration of friendship!  friend class GA;    // Interface functions  inline int    getNoOfFeasible(void) const { return noOfFeasible; }
  inline double getMaxObj(void) const { return *bestobj; }  inline double getMinObj(void) const { return *worstobj; }  inline double getAvgObj(void) const { return *avgobj; }  inline double getMaxFit(void) const { return *maxfit; }  inline double getMinFit(void) const { return *minfit; }  inline double getAvgFit(void) const { return *avgfit; }  inline double getFitVar(void) const { return *varfit; }  inline double getAvgObjChange(void) const { return *avgObjChange; }  inline double getBestObjChange(void) const { return *bestObjChange; }  inline double getFitVarChange(void) const { return *fitVarChange; }  inline double getAvgFitChange(void) const { return *avgFitChange; }  inline double getBestFitChange(void) const { return *bestFitChange; } 
  inline void setNoOfFeasible(int iValue) { noOfFeasible = iValue; }
  inline void setMaxObj(double dValue) { *bestobj = dValue; }
  inline void setMinObj(double dValue) { *worstobj = dValue; }
  inline void setAvgObj(double dValue) { *avgobj = dValue; }
  inline void setMaxFit(double dValue) { *maxfit = dValue; }
  inline void setMinFit(double dValue) { *minfit = dValue; }
  inline void setAvgFit(double dValue) { *avgfit = dValue; }
  inline void setFitVar(double dValue) { *varfit = dValue; }
  inline void setAvgObjChange(double dValue) { *avgObjChange = dValue; }
  inline void setBestObjChange(double dValue) { *bestObjChange = dValue; }
  inline void setFitVarChange(double dValue) { *fitVarChange = dValue; }
  inline void setAvgFitChange(double dValue) { *avgFitChange = dValue; }
  inline void setBestFitChange(double dValue) { *bestFitChange = dValue; } 
  inline double getFitness(const int index) const {return guys[index]->getFitness();}  Individual *getBestIndividual(void) {return bestInd; }
  inline int*   getMPool(void) { return mpool; }
  inline int*	getFreezeMask(void) { return freezeMask; }
  //Common GA operations called on each and every individual  int doEvaluate(void);  void loadPopulationFromFile(void);  void doSelect(void);  void doCrossover(void);  void doMutate(void);  int doLocalSearch(void);  void replacePopulation(void);  void mapObjectiveToFitness(void);  void computeObjStatistics(void);  void computeFitnessStatistics(void);  void scaleFitness(void);  void rankingQuickSort(int *output, int left, int right);  void swap(int& ii, int& jj);    //Freeze and flood operations  void	freeze(int locus);  void	flood( int locus);  // Some operations  Individual *operator[]( int index ) const {    return guys[index];  }    friend std::ostream &operator<< ( std::ostream &out, const Population &pop );  //Some GA operations defined in Population    void shareFitness(void);  void doRTS(void);};class NsgaPopulation : public Population {protected:  NsgaIndividual **combinedGuys;  int *numIndsFront;  int **paretoFront;  int numFronts;  int numFrontChange;public:  // The Big 3  NsgaPopulation(void);  NsgaPopulation(const NsgaPopulation &sourcePop);  ~NsgaPopulation(void);  double getCrowdingDistance(int index) {return combinedGuys[index]->getCrowdingDistance();}  // I think friendship is not derived - so I am redeclaring  friend class GA;  void doNonDominatedSort(int whichGuys);  void computeCrowdingDistance(int whichGuys);  void quickSort(NsgaIndividual **theGuys, int *output, int left, int right, int objID);  void regQSort(double *crowdingDistance, int *output, int left, int right);  void swap(int &ii, int &jj);  void computeObjStatistics(int whichGuys);  void computeFitnessStatistics(int whichGuys);  void mapObjectiveToFitness(int whichGuys);
  inline int getNoOfIndsBestFront(void) const { return numIndsFront[0]; }

  inline int* getNoOfIndsFront(void) { return numIndsFront; }
  inline int** getParetoFront(void) { return paretoFront; }
  inline NsgaIndividual** getCombinedGuys(void) { return combinedGuys; }
  
  inline int getNoOfFronts(void) const { return numFronts; }
  inline int getNoOfFrontChange(void) const { return numFrontChange; }
  inline double getMaxObj(int index) const { return bestobj[index]; }  inline double getMinObj(int index) const { return worstobj[index]; }  inline double getAvgObj(int index) const { return avgobj[index]; }  inline double getMaxFit(int index) const { return maxfit[index]; }  inline double getMinFit(int index) const { return minfit[index]; }  inline double getAvgFit(int index) const { return avgfit[index]; }  inline double getFitVar(int index) const { return varfit[index]; }
  inline void setNoOfFronts(int iValue) { numFronts = iValue; }
  inline void setNoOfFrontChange(int iValue) { numFrontChange = iValue; }
  inline void setMaxObj(int index, double dValue) { bestobj[index] = dValue; }
  inline void setMinObj(int index, double dValue) { worstobj[index] = dValue; }
  inline void setAvgObj(int index, double dValue) { avgobj[index] = dValue; }
  inline void setMaxFit(int index, double dValue) { maxfit[index] = dValue; }
  inline void setMinFit(int index, double dValue) { minfit[index] = dValue; }
  inline void setAvgFit(int index, double dValue) { avgfit[index] = dValue; }
  inline void setFitVar(int index, double dValue) { varfit[index] = dValue; }
};#endif