//package geneticAlgo;import java.util.Comparator;import java.util.Arrays;import java.lang.Math;import java.util.Random;import java.util.ArrayList;import java.util.Collections;public class Main { // returns decimal representation of binary matrix. Note: binary matrix starts with lowest power of 2 public static int bin_to_int(int bin_rep) { int int_rep = 0; for (int i=0; i parents = new ArrayList(); int parents = new int105; for (int j = 0; j < 8; j++) { Random rand = new Random(); int parent = new int5; for (int k = 0; k < parent.length; k++) { parentk = rand.nextInt(2); } parentsj = parent; } System.out.println("Parents"); print_population(parents); double average = avg(parents); System.out.println("Average: " + average); // sort population by fitness and take 5 fittest individuals Arrays.sort(parents, (a, b) -> {return (fitness(b)-fitness(a));}); int new_parents = Arrays.copyOfRange(parents, 0, 5); int generation = 1; while (average < 29) { System.out.println("New parents (generation " + generation + "): "); print_population(new_parents); int count = 0; // generate children from crossover int children = new int205; for (int j = 0; j < new_parents.length; j++) { for (int k = j + 1; k < new_parents.length; k++) { int generated_children = crossover(new_parentsj, new_parentsk); if (generation == 1) { System.out.println("Crossover. Parent 1: " + Arrays.toString(new_parentsj) + " Parent 2: " + Arrays.toString(new_parentsk) + " -> ” + “Child 1: ” + Arrays.toString(generated_children0) + ” Child2: ” + Arrays.toString(generated_children1)); } childrencount = mutate(generated_children0, .05); System.out.println(“Mutation. Generated child: ” + Arrays.toString(generated_children0) + ” -> Actual child: ” + Arrays.toString(childrencount)); count++; childrencount = mutate(generated_children1, .05); System.out.println(“Mutation. Generated child: ” + Arrays.toString(generated_children1) + ” -> Actual child: ” + Arrays.toString(childrencount)); count++; } } System.out.println(“Children: “); print_population(children); average = avg(children); System.out.println(“Average: ” + average); Arrays.sort(children, (a, b) -> { return fitness(b) – fitness(a); }); new_parents = Arrays.copyOfRange(children, 0, 5); generation++; } int soln = new_parents0; System.out.println(“Best solution: ” + bin_to_int(soln) + “. Binary rep: ” + Arrays.toString(soln) + ” fitness: ” + fitness(soln)); return bin_to_int(soln); } public static int problem2() { //ArrayList parents = new ArrayList(); int parents = new int105; for (int j = 0; j < 8; j++) { Random rand = new Random(); int parent = new int5; for (int k = 0; k < parent.length; k++) { parentk = rand.nextInt(2); } parentsj = parent; } System.out.println("Parents"); print_population2(parents); double average = avg_fitness(parents); System.out.println("Average fitness: " + average); // sort population by fitness and take 5 fittest individuals Arrays.sort(parents, (a, b) -> { return (fitness2(b) – fitness2(a)); }); int new_parents = Arrays.copyOfRange(parents, 0, 5); int generation = 1; while (average < -10) { System.out.println("New parents (generation " + generation + "): "); print_population2(new_parents); int count = 0; // generate children from crossover int children = new int205; for (int j = 0; j < new_parents.length; j++) { for (int k = j + 1; k < new_parents.length; k++) { int generated_children = crossover(new_parentsj, new_parentsk); if (generation == 1) { System.out.println("Crossover. Parent 1: " + Arrays.toString(new_parentsj) + " Parent 2: " + Arrays.toString(new_parentsk) + " -> ” + “Child 1: ” + Arrays.toString(generated_children0) + ” Child2: ” + Arrays.toString(generated_children1)); } childrencount = mutate(generated_children0, .05); System.out.println(“Mutation. Generated child: ” + Arrays.toString(generated_children0) + ” -> Actual child: ” + Arrays.toString(childrencount)); count++; childrencount = mutate(generated_children1, .05); System.out.println(“Mutation. Generated child: ” + Arrays.toString(generated_children1) + ” -> Actual child: ” + Arrays.toString(childrencount)); count++; } } System.out.println(“Children: “); print_population2(children); average = avg_fitness(children); System.out.println(“Average fitness: ” + average); Arrays.sort(children, (a, b) -> { return fitness2(b) – fitness2(a); }); new_parents = Arrays.copyOfRange(children, 0, 5); generation++; } int soln = new_parents0; System.out.println(“Best solution: ” + bin_to_int(soln) + “. Binary rep: ” + Arrays.toString(soln) + ” fitness: ” + fitness(soln)); return bin_to_int(soln); } public static void main(String args) { int soln2 = problem2(); }}
