001 /*
002 * JENES
003 * A time asnd memory efficient Java library for genetic algorithms and more
004 * Copyright (C) 2011 Intelligentia srl
005 *
006 * This program is free software: you can redistribute it and/or modify
007 * it under the terms of the GNU General Public License as published by
008 * the Free Software Foundation, either version 3 of the License, or
009 * (at your option) any later version.
010 *
011 * This program is distributed in the hope that it will be useful,
012 * but WITHOUT ANY WARRANTY; without even the implied warranty of
013 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
014 * GNU General Public License for more details.
015 *
016 * You should have received a copy of the GNU General Public License
017 * along with this program. If not, see <http://www.gnu.org/licenses/>.
018 */
019 package jenes.tutorials.old.problem7;
020
021 import java.io.File;
022 import java.io.FileNotFoundException;
023 import java.io.IOException;
024 import jenes.GenerationEventListener;
025 import jenes.GeneticAlgorithm;
026 import jenes.chromosome.BooleanChromosome;
027 import jenes.utils.Random;
028 import jenes.population.Individual;
029 import jenes.population.Population;
030 import jenes.population.Population.Statistics;
031 import jenes.tutorials.utils.Utils;
032 import jenes.utils.CSVLogger;
033 import jenes.statistics.StatisticsLogger;
034 import jenes.tutorials.old.problem6.KnapsackGA;
035 import jenes.utils.XLSLogger;
036
037 /**
038 * A tutorial showing how to log statistics on different media.
039 *
040 * @author Luigi Troiano
041 *
042 * @version 1.3
043 *
044 * @since 1.3
045 */
046 public class KnapsackLoggedProblem {
047
048 private static int POPSIZE=20;
049 private static int GENERATION_LIMIT=100;
050
051 private static final double[] WEIGHTS = {1, 5, 3, 2, 8, 6, 4, 7, 9, 6};
052 private static final double[] UTILITIES = {7, 2, 7, 1, 6, 4, 2, 8, 9, 2};
053
054 private KnapsackGA algorithm;
055 private double[] utilities;
056 private double[] weights;
057
058 private StatisticsLogger csvlogger;
059 private StatisticsLogger xlslogge1;
060 private StatisticsLogger xlslogge2;
061 private XLSLogger xlslogge3;
062 private int exec;
063
064 private final String FOLDER = "files.Tutorial7" + File.separatorChar;
065
066 public KnapsackLoggedProblem(double[] utilities, double[] weights) throws IOException {
067 algorithm = new KnapsackGA(POPSIZE, GENERATION_LIMIT, utilities, weights);
068 this.weights = weights;
069 this.utilities = utilities;
070
071 csvlogger = new StatisticsLogger(
072 new CSVLogger(new String[]{"LegalHighestScore","LegalScoreAvg","LegalScoreDev"}, FOLDER+"knapsackproblem.csv" ) );
073
074 xlslogge1 = new StatisticsLogger(
075 new XLSLogger(new String[]{"LegalHighestScore","LegalScoreAvg","LegalScoreDev"}, FOLDER+"knapsack1.log.xls" ) );
076
077 xlslogge2 = new StatisticsLogger(
078 new XLSLogger(new String[]{"LegalHighestScore", "LegalScoreAvg" , "IllegalScoreAvg"}, FOLDER+"knapsack2.log.xls", FOLDER+"knapsack.tpl.xls" ) );
079
080 xlslogge3 = new XLSLogger(new String[]{"LegalHighestScore", "LegalScoreAvg" , "Run"}, FOLDER+"knapsack3.log.xls");
081
082 }
083
084 @SuppressWarnings("unchecked")
085 public void run() {
086 this.algorithm.evolve();
087
088 Statistics stat=algorithm.getCurrentPopulation().getStatistics();
089 Individual solution=stat.getLegalHighestIndividual();
090 System.out.println(solution.getChromosome());
091 System.out.format("W: %f U: %f\n", algorithm.getWeightOf(solution), algorithm.getUtilityOf(solution) );
092 }
093
094 public double getCapacity() {
095 return this.algorithm.getCapacity();
096 }
097
098 public void setCapacity(double c) {
099 this.algorithm.setCapacity(c);
100 }
101
102 public double[] getUtilities() {
103 return utilities;
104 }
105
106 public double[] getWeights() {
107 return weights;
108 }
109
110 public static KnapsackLoggedProblem build(int n) throws FileNotFoundException, IOException {
111
112 Random r = Random.getInstance();
113
114 double[] utilities = new double[n];
115 for( int i = 0; i < n; ++i ) {
116 utilities[i] = r.nextInt(10);
117 }
118
119 double[] weights = new double[n];
120 for( int i = 0; i < n; ++i ) {
121 weights[i] = r.nextInt(10);
122 }
123
124 return new KnapsackLoggedProblem(utilities, weights);
125 }
126
127 public static void main(String[] args) throws FileNotFoundException, IOException {
128
129 Utils.printHeader();
130 System.out.println();
131
132 System.out.println("TUTORIAL 7:");
133 System.out.println("Logging the Knapsack Problem.");
134 System.out.println();
135
136 final KnapsackLoggedProblem prb = KnapsackLoggedProblem.build(20);
137
138 System.out.println("Utilities: " + toString(prb.getUtilities()) );
139 System.out.println(" Weights: " + toString(prb.getWeights()) );
140 System.out.println();
141
142 GenerationEventListener<BooleanChromosome> logger1 = new GenerationEventListener<BooleanChromosome>() {
143
144 public void onGeneration(GeneticAlgorithm ga, long time) {
145 Population.Statistics stats = ga.getCurrentPopulation().getStatistics();
146
147 prb.csvlogger.record(stats);
148 prb.xlslogge1.record(stats);
149 prb.xlslogge2.record(stats);
150
151 }
152
153 };
154
155 prb.algorithm.addGenerationEventListener(logger1);
156
157
158 System.out.println("50 random elements, capacity 50");
159 prb.setCapacity(50);
160 prb.run();
161 System.out.println();
162
163 System.out.println("Saving the logs ...");
164 prb.csvlogger.close();
165 prb.xlslogge1.close();
166 prb.xlslogge2.close();
167 System.out.println("Done.");
168
169 prb.algorithm.removeGenerationEventListener(logger1);
170
171 GenerationEventListener<BooleanChromosome> logger2 = new GenerationEventListener<BooleanChromosome>() {
172 public void onGeneration(GeneticAlgorithm ga, long time) {
173 Population.Statistics stats = ga.getCurrentPopulation().getStatistics();
174
175 prb.xlslogge3.put("LegalHighestScore", stats.getLegalHighestScore());
176 prb.xlslogge3.put("LegalScoreAvg", stats.getLegalScoreAvg());
177 prb.xlslogge3.put("Run", prb.exec);
178
179 prb.xlslogge3.log();
180 }
181
182 };
183
184 prb.algorithm.addGenerationEventListener(logger2);
185
186 System.out.println();
187 System.out.println("Repeating 10 times: 20 random elements, capacity 50");
188 for( prb.exec = 0; prb.exec < 10; ++prb.exec) {
189 System.out.println((prb.exec+1) + " of 10");
190 prb.run();
191 }
192 prb.xlslogge3.close();
193 System.out.println("Done.");
194 }
195
196 private static String toString(double[] values) {
197 String s = "[";
198 for(int i = 0; i < values.length; ++i ){
199 s += values[i]+ (i < values.length-1 ? " " : "]");
200 }
201 return s;
202 }
203
204 }
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