SimpleEquation.java

// SimpleEquation.java
// From Classic Computer Science Problems in Java Chapter 5
// Copyright 2020 David Kopec
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

package chapter5;

import java.util.ArrayList;
import java.util.List;
import java.util.Random;

public class SimpleEquation extends Chromosome<SimpleEquation> {
	private int x, y;

	private static final int MAX_START = 100;

	public SimpleEquation(int x, int y) {
		this.x = x;
		this.y = y;
	}

	public static SimpleEquation randomInstance() {
		Random random = new Random();
		return new SimpleEquation(random.nextInt(MAX_START), random.nextInt(MAX_START));
	}

	// 6x - x^2 + 4y - y^2
	@Override
	public double fitness() {
		return 6 * x - x * x + 4 * y - y * y;
	}

	@Override
	public List<SimpleEquation> crossover(SimpleEquation other) {
		SimpleEquation child1 = new SimpleEquation(x, other.y);
		SimpleEquation child2 = new SimpleEquation(other.x, y);
		return List.of(child1, child2);
	}

	@Override
	public void mutate() {
		Random random = new Random();
		if (random.nextDouble() > 0.5) { // mutate x
			if (random.nextDouble() > 0.5) {
				x += 1;
			} else {
				x -= 1;
			}
		} else { // otherwise mutate y
			if (random.nextDouble() > 0.5) {
				y += 1;
			} else {
				y -= 1;
			}
		}

	}

	@Override
	public SimpleEquation copy() {
		return new SimpleEquation(x, y);
	}

	@Override
	public String toString() {
		return "X: " + x + " Y: " + y + " Fitness: " + fitness();
	}

	public static void main(String[] args) {
		ArrayList<SimpleEquation> initialPopulation = new ArrayList<>();
		final int POPULATION_SIZE = 20;
		final int GENERATIONS = 100;
		final double THRESHOLD = 13.0;
		for (int i = 0; i < POPULATION_SIZE; i++) {
			initialPopulation.add(SimpleEquation.randomInstance());
		}
		GeneticAlgorithm<SimpleEquation> ga = new GeneticAlgorithm<>(
				initialPopulation,
				0.1, 0.7, GeneticAlgorithm.SelectionType.TOURNAMENT);
		SimpleEquation result = ga.run(GENERATIONS, THRESHOLD);
		System.out.println(result);
	}

}