trans/graphhopper-jsprit
1
0
Fork 0
mirror of https://github.com/graphhopper/jsprit.git synced 2020-01-24 07:45:05 +01:00
Code Issues Releases Wiki Activity

added examples to illustrate

Browse source 
analysis.toolbox.ComputationalLaborator.java
This commit is contained in:
oblonski 2014-04-15 13:22:47 +02:00
parent 514d81713f
commit 5720a0eae2
3 changed files with 449 additions and 0 deletions
Download patch file Download diff file Expand all files Collapse all files

136
jsprit-examples/src/main/java/jsprit/examples/ComputationalExperiments_randomVariations.java Normal file
View file

@ -0,0 +1,136 @@
/*******************************************************************************
* Copyright (C) 2013 Stefan Schroeder
*
* This library is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 3.0 of the License, or (at your option) any later version.
*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with this library. If not, see <http://www.gnu.org/licenses/>.
******************************************************************************/
package jsprit.examples;
import java.util.Collection;
import jsprit.analysis.toolbox.ComputationalLaboratory;
import jsprit.analysis.toolbox.ComputationalLaboratory.CalculationListener;
import jsprit.analysis.toolbox.XYLineChartBuilder;
import jsprit.core.algorithm.VehicleRoutingAlgorithm;
import jsprit.core.algorithm.VehicleRoutingAlgorithmFactory;
import jsprit.core.algorithm.io.VehicleRoutingAlgorithms;
import jsprit.core.algorithm.listener.IterationStartsListener;
import jsprit.core.problem.VehicleRoutingProblem;
import jsprit.core.problem.solution.VehicleRoutingProblemSolution;
import jsprit.core.util.BenchmarkInstance;
import jsprit.core.util.Solutions;
import jsprit.instance.reader.SolomonReader;
import jsprit.util.Examples;
/**
* Based on Solomon's R101 instance
*
* @author schroeder
*
*/
public class ComputationalExperiments_randomVariations {
public static void main(String[] args) {
/*
* some preparation - create output folder
*/
Examples.createOutputFolder();
/*
* Build the problem.
*
* But define a problem-builder first.
*/
VehicleRoutingProblem.Builder vrpBuilder = VehicleRoutingProblem.Builder.newInstance();
/*
* A solomonReader reads solomon-instance files, and stores the required information in the builder.
*/
new SolomonReader(vrpBuilder).read("input/R101.txt");
/*
* Finally, the problem can be built. By default, transportCosts are crowFlyDistances (as usually used for vrp-instances).
*/
VehicleRoutingProblem vrp = vrpBuilder.build();
/*
* Create ComputationalLaboratory
*/
ComputationalLaboratory computationalLab = new ComputationalLaboratory();
/*
* add benchmarking instance
*/
computationalLab.addInstance("SolomonR101", vrp);
/*
* add algorithms through factories
*
*
*
*/
computationalLab.addAlgorithmFactory("schrimpfAcceptance", new VehicleRoutingAlgorithmFactory() {
@Override
public VehicleRoutingAlgorithm createAlgorithm(VehicleRoutingProblem vrp) {
VehicleRoutingAlgorithm vra = VehicleRoutingAlgorithms.readAndCreateAlgorithm(vrp, "input/algorithmConfigWithSchrimpfAcceptance.xml");
vra.setNuOfIterations(4000);
return vra;
}
});
/*
* run schrimpfAcceptance 5 times (and thus each with another seed of random number generator)
*/
computationalLab.setNuOfRuns(5);
/*
* plot search progress of different algorithms
*/
final XYLineChartBuilder chartBuilder = XYLineChartBuilder.newInstance("random variations", "iterations", "costs");
computationalLab.addListener(new CalculationListener() {
@Override
public void calculationStarts(BenchmarkInstance p, final String algorithmName,VehicleRoutingAlgorithm algorithm, final int run) {
algorithm.addListener(new IterationStartsListener() {
@Override
public void informIterationStarts(int i, VehicleRoutingProblem problem,Collection<VehicleRoutingProblemSolution> solutions) {
/*
* since there will be more than 1 run and we want to plot each run, we need to specify an apropriate
* XYSeries-name. Thus we add run to algorithmName.
*/
chartBuilder.addData(algorithmName+"_"+run, i, Solutions.bestOf(solutions).getCost());
}
});
}
@Override
public void calculationEnds(BenchmarkInstance p, String algorithmName,VehicleRoutingAlgorithm algorithm, int run,Collection<VehicleRoutingProblemSolution> solutions) {}
});
computationalLab.setThreads(2);
/*
* run the experiments
*/
computationalLab.run();
/*
* plot the lineChart
*/
XYLineChartBuilder.saveChartAsPNG(chartBuilder.build(), "output/computationalStudies_randomVariations.png");
}
}

173
jsprit-examples/src/main/java/jsprit/examples/ComputationalExperiments_randomVariations_and_nuOfIterations.java Normal file
View file

@ -0,0 +1,173 @@
/*******************************************************************************
* Copyright (C) 2013 Stefan Schroeder
*
* This library is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 3.0 of the License, or (at your option) any later version.
*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with this library. If not, see <http://www.gnu.org/licenses/>.
******************************************************************************/
package jsprit.examples;
import java.util.Collection;
import jsprit.analysis.toolbox.ComputationalLaboratory;
import jsprit.analysis.toolbox.ComputationalLaboratory.CalculationListener;
import jsprit.analysis.toolbox.ComputationalLaboratory.DataCollector;
import jsprit.analysis.toolbox.XYLineChartBuilder;
import jsprit.core.algorithm.VehicleRoutingAlgorithm;
import jsprit.core.algorithm.VehicleRoutingAlgorithmFactory;
import jsprit.core.algorithm.io.VehicleRoutingAlgorithms;
import jsprit.core.problem.VehicleRoutingProblem;
import jsprit.core.problem.solution.VehicleRoutingProblemSolution;
import jsprit.core.util.BenchmarkInstance;
import jsprit.core.util.Solutions;
import jsprit.instance.reader.SolomonReader;
import jsprit.util.Examples;
/**
* Based on Solomon's R101 instance
*
* @author schroeder
*
*/
public class ComputationalExperiments_randomVariations_and_nuOfIterations {
public static void main(String[] args) {
/*
* some preparation - create output folder
*/
Examples.createOutputFolder();
/*
* Build the problem.
*
* But define a problem-builder first.
*/
VehicleRoutingProblem.Builder vrpBuilder = VehicleRoutingProblem.Builder.newInstance();
/*
* A solomonReader reads solomon-instance files, and stores the required information in the builder.
*/
new SolomonReader(vrpBuilder).read("input/R101.txt");
/*
* Finally, the problem can be built. By default, transportCosts are crowFlyDistances (as usually used for vrp-instances).
*/
VehicleRoutingProblem vrp = vrpBuilder.build();
/*
* Create ComputationalLaboratory
*/
ComputationalLaboratory computationalLab = new ComputationalLaboratory();
/*
* add benchmarking instance
*/
computationalLab.addInstance("SolomonR101", vrp);
/*
* add algorithms through factories
*
*
*
*/
computationalLab.addAlgorithmFactory("schrimpfAcceptance_1", getAlgorithmFactory(1));
computationalLab.addAlgorithmFactory("schrimpfAcceptance_100", getAlgorithmFactory(100));
computationalLab.addAlgorithmFactory("schrimpfAcceptance_500", getAlgorithmFactory(500));
computationalLab.addAlgorithmFactory("schrimpfAcceptance_1000", getAlgorithmFactory(1000));
computationalLab.addAlgorithmFactory("schrimpfAcceptance_2000", getAlgorithmFactory(2000));
computationalLab.addAlgorithmFactory("schrimpfAcceptance_4000", getAlgorithmFactory(4000));
computationalLab.addAlgorithmFactory("schrimpfAcceptance_8000", getAlgorithmFactory(8000));
computationalLab.addAlgorithmFactory("schrimpfAcceptance_12000", getAlgorithmFactory(12000));
/*
* run schrimpfAcceptance 5 times (and thus each with another seed of random number generator)
*/
computationalLab.setNuOfRuns(5);
/*
* plot search progress of different algorithms
*/
final DataCollector dataCollector = new DataCollector();
computationalLab.addListener(new CalculationListener() {
@Override
public void calculationStarts(BenchmarkInstance p, final String algorithmName,VehicleRoutingAlgorithm algorithm, final int run) {}
@Override
public void calculationEnds(BenchmarkInstance p, String algorithmName,VehicleRoutingAlgorithm algorithm, int run,Collection<VehicleRoutingProblemSolution> solutions) {
dataCollector.addDate("R101", algorithmName, run, "costs", Solutions.bestOf(solutions).getCost());
}
});
computationalLab.setThreads(2);
/*
* run the experiments
*/
computationalLab.run();
/*
* plot min, avg and max
*/
XYLineChartBuilder chartBuilder = XYLineChartBuilder.newInstance("variations with iterations", "iterations", "costs");
for(String algorithmName : computationalLab.getAlgorithmNames()){
String[] nameTokens = algorithmName.split("_");
int iteration = Integer.parseInt(nameTokens[1]);
chartBuilder.addData("min", iteration, min(dataCollector.getData("R101", algorithmName, "costs")));
chartBuilder.addData("max", iteration, max(dataCollector.getData("R101", algorithmName, "costs")));
chartBuilder.addData("avg", iteration, avg(dataCollector.getData("R101", algorithmName, "costs")));
}
XYLineChartBuilder.saveChartAsPNG(chartBuilder.build(), "output/computationalStudies_min_max_avg.png");
}
public static double min(Collection<Double> doubles){
double min = Double.MAX_VALUE;
for(Double d : doubles){
if(d<min) min=d;
}
return min;
}
public static double max(Collection<Double> doubles){
double max = 0.;
for(Double d : doubles){
if(d>max) max=d;
}
return max;
}
public static double avg(Collection<Double> doubles){
if(doubles.isEmpty()) return 0.;
double sum = 0.;
for(Double d : doubles){
sum+=d;
}
return sum/(double)doubles.size();
}
private static VehicleRoutingAlgorithmFactory getAlgorithmFactory(final int iterations) {
return new VehicleRoutingAlgorithmFactory() {
@Override
public VehicleRoutingAlgorithm createAlgorithm(VehicleRoutingProblem vrp) {
VehicleRoutingAlgorithm vra = VehicleRoutingAlgorithms.readAndCreateAlgorithm(vrp, "input/algorithmConfigWithSchrimpfAcceptance.xml");
vra.setNuOfIterations(iterations);
return vra;
}
};
}
}

140
jsprit-examples/src/main/java/jsprit/examples/ComputationalExperiments_schrimpf_vs_greedy.java Normal file
View file

@ -0,0 +1,140 @@
/*******************************************************************************
* Copyright (C) 2013 Stefan Schroeder
*
* This library is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 3.0 of the License, or (at your option) any later version.
*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with this library. If not, see <http://www.gnu.org/licenses/>.
******************************************************************************/
package jsprit.examples;
import java.util.Collection;
import jsprit.analysis.toolbox.ComputationalLaboratory;
import jsprit.analysis.toolbox.ComputationalLaboratory.CalculationListener;
import jsprit.analysis.toolbox.XYLineChartBuilder;
import jsprit.core.algorithm.VehicleRoutingAlgorithm;
import jsprit.core.algorithm.VehicleRoutingAlgorithmFactory;
import jsprit.core.algorithm.io.VehicleRoutingAlgorithms;
import jsprit.core.algorithm.listener.IterationStartsListener;
import jsprit.core.problem.VehicleRoutingProblem;
import jsprit.core.problem.solution.VehicleRoutingProblemSolution;
import jsprit.core.util.BenchmarkInstance;
import jsprit.core.util.Solutions;
import jsprit.instance.reader.SolomonReader;
import jsprit.util.Examples;
/**
* Based on Solomon's R101 instance
*
* @author schroeder
*
*/
public class ComputationalExperiments_schrimpf_vs_greedy {
public static void main(String[] args) {
/*
* some preparation - create output folder
*/
Examples.createOutputFolder();
/*
* Build the problem.
*
* But define a problem-builder first.
*/
VehicleRoutingProblem.Builder vrpBuilder = VehicleRoutingProblem.Builder.newInstance();
/*
* A solomonReader reads solomon-instance files, and stores the required information in the builder.
*/
new SolomonReader(vrpBuilder).read("input/R101.txt");
/*
* Finally, the problem can be built. By default, transportCosts are crowFlyDistances (as usually used for vrp-instances).
*/
VehicleRoutingProblem vrp = vrpBuilder.build();
/*
* Create ComputationalLaboratory
*/
ComputationalLaboratory computationalLab = new ComputationalLaboratory();
/*
* add benchmarking instance
*/
computationalLab.addInstance("SolomonR101", vrp);
/*
* add algorithms through factories
*
*
* Define 3 algorithms
* - algorithmsConfigWithSchrimpfAcceptance (4000 iterations)
* - algorithmsConfigWithGreedyAcceptance (4000 iterations)
*
*/
computationalLab.addAlgorithmFactory("schrimpfAcceptance", new VehicleRoutingAlgorithmFactory() {
@Override
public VehicleRoutingAlgorithm createAlgorithm(VehicleRoutingProblem vrp) {
VehicleRoutingAlgorithm vra = VehicleRoutingAlgorithms.readAndCreateAlgorithm(vrp, "input/algorithmConfigWithSchrimpfAcceptance.xml");
vra.setNuOfIterations(4000);
return vra;
}
});
computationalLab.addAlgorithmFactory("greedyAcceptance", new VehicleRoutingAlgorithmFactory() {
@Override
public VehicleRoutingAlgorithm createAlgorithm(VehicleRoutingProblem vrp) {
VehicleRoutingAlgorithm vra = VehicleRoutingAlgorithms.readAndCreateAlgorithm(vrp, "input/algorithmConfig_solomon.xml");
vra.setNuOfIterations(4000);
return vra;
}
});
/*
* plot search progress of different algorithms
*/
final XYLineChartBuilder chartBuilder = XYLineChartBuilder.newInstance("schrimpf vs greedy", "iterations", "costs");
computationalLab.addListener(new CalculationListener() {
@Override
public void calculationStarts(BenchmarkInstance p, final String algorithmName,VehicleRoutingAlgorithm algorithm, int run) {
algorithm.addListener(new IterationStartsListener() {
@Override
public void informIterationStarts(int i, VehicleRoutingProblem problem,Collection<VehicleRoutingProblemSolution> solutions) {
chartBuilder.addData(algorithmName, i, Solutions.bestOf(solutions).getCost());
}
});
}
@Override
public void calculationEnds(BenchmarkInstance p, String algorithmName,VehicleRoutingAlgorithm algorithm, int run,Collection<VehicleRoutingProblemSolution> solutions) {}
});
computationalLab.setThreads(2);
/*
* run the experiments
*/
computationalLab.run();
/*
* plot the lineChart
*/
XYLineChartBuilder.saveChartAsPNG(chartBuilder.build(), "output/computationalStudies_schrimpf_vs_greedy.png");
}
}