geneticalgorithmgui.java

基于求函数f(x,y,z)=xyz*sin(xyz)最大值问题的演示程序 解压后在命令行输入：java -jar genetic_algorithm.jar

package edu.zsu.zouang.genetic.gui;

import java.awt.Dimension;
import java.awt.event.ActionEvent;
import java.awt.event.ActionListener;

import javax.swing.JButton;
import javax.swing.JLabel;
import javax.swing.JOptionPane;
import javax.swing.JPanel;
import javax.swing.JProgressBar;
import javax.swing.JTextField;
import javax.swing.SwingUtilities;
import javax.swing.border.TitledBorder;

import edu.zsu.zouang.genetic.GenerationDetail;
import edu.zsu.zouang.genetic.GeneticAlgorithm;

public class GeneticAlgorithmGUI extends javax.swing.JFrame {

	/**
	 * 
	 */
	private static final long serialVersionUID = 5978534001656130751L;

	private JTextField generationText;

	private JTextField populationText;

	private JTextField mutationText;

	private JTextField crossText;

	private JLabel generationLabel;

	private JLabel averageFitnessLabel;

	private JLabel maxFitnessLabel;

	private JLabel minFitnessLabel;

	private JProgressBar progressBar;

	private GeneticAlgorithm ga = null;

	public GeneticAlgorithmGUI() {
		super();
		setDefaultCloseOperation(DISPOSE_ON_CLOSE);
		setResizable(false);
		setTitle("遗传算法实验");
		getContentPane().setLayout(null);
		setSize(500, 358);

		JPanel configPanel;
		configPanel = new JPanel();
		configPanel.setLayout(null);
		configPanel.setBounds(10, 10, 472, 148);
		getContentPane().add(configPanel);
		configPanel.setBorder(new TitledBorder(null, "配置信息",
				TitledBorder.DEFAULT_JUSTIFICATION,
				TitledBorder.DEFAULT_POSITION, null, null));

		final JLabel label_5 = new JLabel();
		label_5.setBounds(10, 27, 60, 20);
		configPanel.add(label_5);
		label_5.setText("交配概率");

		final JLabel label_6 = new JLabel();
		label_6.setText("变异概率");
		label_6.setBounds(10, 53, 60, 20);
		configPanel.add(label_6);

		final JLabel label_7 = new JLabel();
		label_7.setText("种群规模");
		label_7.setBounds(10, 79, 60, 20);
		configPanel.add(label_7);

		final JLabel label_8 = new JLabel();
		label_8.setText("遗传代数");
		label_8.setBounds(10, 105, 60, 20);
		configPanel.add(label_8);

		crossText = new JTextField();
		crossText.setText("0.9");
		crossText.setAutoscrolls(false);
		crossText.setToolTipText("种群个体之间的交配概率");
		crossText.setBounds(100, 25, 186, 20);
		configPanel.add(crossText);

		mutationText = new JTextField();
		mutationText.setText("0.01");
		mutationText.setAutoscrolls(false);
		mutationText.setToolTipText("种群个体的变异概率");
		mutationText.setBounds(100, 54, 186, 20);
		configPanel.add(mutationText);

		populationText = new JTextField();
		populationText.setText("300");
		populationText.setAutoscrolls(false);
		populationText.setToolTipText("种群个体的数量");
		populationText.setBounds(100, 80, 186, 20);
		configPanel.add(populationText);

		generationText = new JTextField();
		generationText.setText("50");
		generationText.setAutoscrolls(false);
		generationText.setToolTipText("进化的次数");
		generationText.setBounds(100, 106, 186, 20);
		configPanel.add(generationText);

		final JButton startButton = new JButton();
		startButton.addActionListener(new ActionListener() {
			public void actionPerformed(ActionEvent e) {
				String crossPossibility = crossText.getText();
				String mutaionPossibility = mutationText.getText();
				String population = populationText.getText();
				final String generation = generationText.getText();
				try {
					ga = new GeneticAlgorithm(Integer.valueOf(population), 0.0,
							Double.valueOf(crossPossibility), Double
									.valueOf(mutaionPossibility), 24);
				} catch (NumberFormatException e1) {
					// TODO Auto-generated catch block
					JOptionPane.showMessageDialog(getContentPane(), "数字格式不合法!","错误", JOptionPane.ERROR_MESSAGE);
				}
				GeneticAlgorithmThread thread = new GeneticAlgorithmThread(Integer.valueOf(generation));
				new Thread(thread).start();
			}
		});
		startButton.setText("开始");
		startButton.setBounds(331, 26, 99, 23);
		configPanel.add(startButton);

		final JButton closeButton = new JButton();
		closeButton.addActionListener(new ActionListener() {
			public void actionPerformed(ActionEvent e) {
				JOptionPane.showMessageDialog(getContentPane(),
						GeneticAlgorithmReportGenerator.createGeneticAlgorithmReportPanel(), "遗传算法报告",
						JOptionPane.PLAIN_MESSAGE);
			}
		});
		closeButton.setText("生成报告");
		closeButton.setBounds(331, 64, 99, 23);
		configPanel.add(closeButton);

		final JButton aboutButton = new JButton();
		aboutButton.addActionListener(new ActionListener() {
			public void actionPerformed(ActionEvent e) {
				JOptionPane
						.showMessageDialog(
								getContentPane(),
								"版本:\t  v1.0\n作者:\t  邹昂\n专业:\t  软件生产技术\n学号:\t  04382036",
								"关于", JOptionPane.INFORMATION_MESSAGE);
			}
		});
		aboutButton.setText("关于");
		aboutButton.setBounds(331, 104, 99, 23);
		configPanel.add(aboutButton);

		final JPanel detailPanel = new JPanel();
		detailPanel.setLayout(null);
		detailPanel.setBorder(new TitledBorder(null, "详细信息",
				TitledBorder.DEFAULT_JUSTIFICATION,
				TitledBorder.DEFAULT_POSITION, null, null));
		detailPanel.setBounds(10, 193, 472, 123);
		getContentPane().add(detailPanel);

		final JLabel label_2 = new JLabel();
		label_2.setText("当前代数");
		label_2.setBounds(10, 25, 84, 15);
		detailPanel.add(label_2);

		final JLabel label = new JLabel();
		label.setText("平均适应值");
		label.setBounds(10, 46, 84, 15);
		detailPanel.add(label);

		final JLabel label_1 = new JLabel();
		label_1.setText("最大适应值");
		label_1.setBounds(10, 67, 84, 15);
		detailPanel.add(label_1);

		final JLabel label_3 = new JLabel();
		label_3.setText("最小适应值");
		label_3.setBounds(10, 88, 84, 15);
		detailPanel.add(label_3);

		generationLabel = new JLabel();
		generationLabel.setText("0");
		generationLabel.setBounds(119, 25, 164, 15);
		detailPanel.add(generationLabel);

		averageFitnessLabel = new JLabel();
		averageFitnessLabel.setText("0.0");
		averageFitnessLabel.setBounds(119, 46, 164, 15);
		detailPanel.add(averageFitnessLabel);

		maxFitnessLabel = new JLabel();
		maxFitnessLabel.setText("0.0");
		maxFitnessLabel.setBounds(119, 67, 164, 15);
		detailPanel.add(maxFitnessLabel);

		minFitnessLabel = new JLabel();
		minFitnessLabel.setText("0.0");
		minFitnessLabel.setBounds(119, 88, 164, 15);
		detailPanel.add(minFitnessLabel);

		progressBar = new JProgressBar();
		progressBar.setStringPainted(true);
		progressBar.setOpaque(true);
		progressBar.setBounds(10, 164, 472, 18);
		getContentPane().add(progressBar);
		getContentPane().setPreferredSize(new Dimension(500, 358));
	}

	public class GeneticAlgorithmThread extends Thread implements Runnable {
		private int times;

		public GeneticAlgorithmThread(int times) {
			this.times = times;
		}

		@Override
		public void run() {
			// TODO Auto-generated method stub
			super.run();
			for (int i = 0; i < times; i++) {
				ga.crossoverPopulation();
				SwingUtilities.invokeLater(new Runnable() {
					public void run() {
						// TODO Auto-generated method stub
						GenerationDetail detail = ga.getDetail();
						generationLabel.setText(String.valueOf(detail.getGeneration()));
						averageFitnessLabel.setText(String.valueOf(detail.getAverageFitness()));
						maxFitnessLabel.setText(String.valueOf(detail	.getMaxFitness()));
						minFitnessLabel.setText(String.valueOf(detail.getMinFitness()));
						progressBar.setValue(100 * (detail.getGeneration())/ Integer.valueOf(times));
					}
				});
			}
		}
	}
}