Can this Java code be converted to c++ ? and if it can be then convert it.

import java.util.Random;

//Main class public class SimpleDemoGA {

Population population = new Population(); Individual fittest; Individual secondFittest; int generationCount = 0;

public static void main(String[] args) { Random rn = new Random(); SimpleDemoGA demo = new SimpleDemoGA(); //Initialize population demo.population.initializePopulation(10); //Calculate fitness of each individual demo.population.calculateFitness(); System.out.println("Generation: " + demo.generationCount + " Fittest: " + demo.population.fittest); //While population gets an individual with maximum fitness while (demo.population.fittest < 5) { ++demo.generationCount; //Do selection demo.selection(); //Do crossover demo.crossover(); //Do mutation under a random probability if (rn.nextInt()%7 < 5) { demo.mutation(); } //Add fittest offspring to population demo.addFittestOffspring(); //Calculate new fitness value demo.population.calculateFitness(); System.out.println("Generation: " + demo.generationCount + " Fittest: " + demo.population.fittest); } System.out.println(" Solution found in generation " + demo.generationCount); System.out.println("Fitness: "+demo.population.getFittest().fitness); System.out.print("Genes: "); for (int i = 0; i < 5; i++) { System.out.print(demo.population.getFittest().genes[i]); } System.out.println(""); }

//Selection void selection() { //Select the most fittest individual fittest = population.getFittest(); //Select the second most fittest individual secondFittest = population.getSecondFittest(); }

//Crossover void crossover() { Random rn = new Random(); //Select a random crossover point int crossOverPoint = rn.nextInt(population.individuals[0].geneLength); //Swap values among parents for (int i = 0; i < crossOverPoint; i++) { int temp = fittest.genes[i]; fittest.genes[i] = secondFittest.genes[i]; secondFittest.genes[i] = temp; } }

//Mutation void mutation() { Random rn = new Random(); //Select a random mutation point int mutationPoint = rn.nextInt(population.individuals[0].geneLength); //Flip values at the mutation point if (fittest.genes[mutationPoint] == 0) { fittest.genes[mutationPoint] = 1; } else { fittest.genes[mutationPoint] = 0; } mutationPoint = rn.nextInt(population.individuals[0].geneLength); if (secondFittest.genes[mutationPoint] == 0) { secondFittest.genes[mutationPoint] = 1; } else { secondFittest.genes[mutationPoint] = 0; } }

//Get fittest offspring Individual getFittestOffspring() { if (fittest.fitness > secondFittest.fitness) { return fittest; } return secondFittest; }

//Replace least fittest individual from most fittest offspring void addFittestOffspring() { //Update fitness values of offspring fittest.calcFitness(); secondFittest.calcFitness(); //Get index of least fit individual int leastFittestIndex = population.getLeastFittestIndex(); //Replace least fittest individual from most fittest offspring population.individuals[leastFittestIndex] = getFittestOffspring(); }

}

//Individual class class Individual {

int fitness = 0; int[] genes = new int[5]; int geneLength = 5;

public Individual() { Random rn = new Random(); //Set genes randomly for each individual for (int i = 0; i < genes.length; i++) { genes[i] = Math.abs(rn.nextInt() % 2); } fitness = 0; }

//Calculate fitness public void calcFitness() { fitness = 0; for (int i = 0; i < 5; i++) { if (genes[i] == 1) { ++fitness; } } }

}

//Population class class Population {

int popSize = 10; Individual[] individuals = new Individual[10]; int fittest = 0;

//Initialize population public void initializePopulation(int size) { for (int i = 0; i < individuals.length; i++) { individuals[i] = new Individual(); } }

//Get the fittest individual public Individual getFittest() { int maxFit = Integer.MIN_VALUE; int maxFitIndex = 0; for (int i = 0; i < individuals.length; i++) { if (maxFit <= individuals[i].fitness) { maxFit = individuals[i].fitness; maxFitIndex = i; } } fittest = individuals[maxFitIndex].fitness; return individuals[maxFitIndex]; }

//Get the second most fittest individual public Individual getSecondFittest() { int maxFit1 = 0; int maxFit2 = 0; for (int i = 0; i < individuals.length; i++) { if (individuals[i].fitness > individuals[maxFit1].fitness) { maxFit2 = maxFit1; maxFit1 = i; } else if (individuals[i].fitness > individuals[maxFit2].fitness) { maxFit2 = i; } } return individuals[maxFit2]; }

//Get index of least fittest individual public int getLeastFittestIndex() { int minFitVal = Integer.MAX_VALUE; int minFitIndex = 0; for (int i = 0; i < individuals.length; i++) { if (minFitVal >= individuals[i].fitness) { minFitVal = individuals[i].fitness; minFitIndex = i; } } return minFitIndex; }

//Calculate fitness of each individual public void calculateFitness() { for (int i = 0; i < individuals.length; i++) { individuals[i].calcFitness(); } getFittest(); }

}