org.drools.planner.benchmark.core.ProblemBenchmark Maven / Gradle / Ivy
Go to download
Show more of this group Show more artifacts with this name
Show all versions of drools-planner-core Show documentation
Show all versions of drools-planner-core Show documentation
Drools Planner optimizes automated planning by combining metaheuristic search algorithms with rule
engine powered score calculation. This is the drools-planner-core module which contains metaheuristic
algorithms.
/*
* Copyright 2011 JBoss Inc
*
* 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 org.drools.planner.benchmark.core;
import java.io.File;
import java.util.List;
import org.drools.planner.benchmark.api.ProblemIO;
import org.drools.planner.benchmark.core.statistic.ProblemStatistic;
import org.drools.planner.config.termination.TerminationConfig;
import org.drools.planner.core.Solver;
import org.drools.planner.core.domain.solution.SolutionDescriptor;
import org.drools.planner.core.solution.Solution;
import org.drools.planner.core.solver.DefaultSolver;
import org.drools.planner.core.solver.DefaultSolverScope;
/**
* Represents one problem instance (a data set) benchmarked on multiple solvers.
*/
public class ProblemBenchmark {
private String name = null;
private ProblemIO problemIO = null;
private File inputSolutionFile = null;
private File outputSolutionFilesDirectory = null;
private List problemStatisticList = null;
private List plannerBenchmarkResultList = null;
private PlannerBenchmarkResult winningPlannerBenchmarkResult = null;
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
public ProblemIO getProblemIO() {
return problemIO;
}
public void setProblemIO(ProblemIO problemIO) {
this.problemIO = problemIO;
}
public File getInputSolutionFile() {
return inputSolutionFile;
}
public void setInputSolutionFile(File inputSolutionFile) {
this.inputSolutionFile = inputSolutionFile;
}
public File getOutputSolutionFilesDirectory() {
return outputSolutionFilesDirectory;
}
public void setOutputSolutionFilesDirectory(File outputSolutionFilesDirectory) {
this.outputSolutionFilesDirectory = outputSolutionFilesDirectory;
}
public List getProblemStatisticList() {
return problemStatisticList;
}
public void setProblemStatisticList(List problemStatisticList) {
this.problemStatisticList = problemStatisticList;
}
public List getPlannerBenchmarkResultList() {
return plannerBenchmarkResultList;
}
public void setPlannerBenchmarkResultList(List plannerBenchmarkResultList) {
this.plannerBenchmarkResultList = plannerBenchmarkResultList;
}
public PlannerBenchmarkResult getWinningPlannerBenchmarkResult() {
return winningPlannerBenchmarkResult;
}
public void setWinningPlannerBenchmarkResult(PlannerBenchmarkResult winningPlannerBenchmarkResult) {
this.winningPlannerBenchmarkResult = winningPlannerBenchmarkResult;
}
// ************************************************************************
// Benchmark methods
// ************************************************************************
public void benchmarkingStarted() {
}
public void benchmark() {
for (PlannerBenchmarkResult result : plannerBenchmarkResultList) {
SolverBenchmark solverBenchmark = result.getSolverBenchmark();
// Intentionally create a fresh solver for every result to reset Random, tabu lists, ...
Solver solver = solverBenchmark.getSolverConfig().buildSolver();
for (ProblemStatistic statistic : problemStatisticList) {
statistic.addListener(solver, solverBenchmark.getName());
}
solver.setPlanningProblem(readPlanningProblem());
solver.solve();
Solution outputSolution = solver.getBestSolution();
result.setTimeMillisSpend(solver.getTimeMillisSpend());
DefaultSolverScope solverScope = ((DefaultSolver) solver).getSolverScope();
result.setCalculateCount(solverScope.getCalculateCount());
result.setScore(outputSolution.getScore());
SolutionDescriptor solutionDescriptor = ((DefaultSolver) solver).getSolutionDescriptor();
result.setPlanningEntityCount(solutionDescriptor.getPlanningEntityCount(outputSolution));
result.setProblemScale(solutionDescriptor.getProblemScale(outputSolution));
for (ProblemStatistic statistic : problemStatisticList) {
statistic.removeListener(solver, solverBenchmark.getName());
}
writeSolution(result, outputSolution);
}
}
public long warmUp(long startingTimeMillis, long warmUpTimeMillisSpend, long timeLeft) {
for (PlannerBenchmarkResult result : plannerBenchmarkResultList) {
SolverBenchmark solverBenchmark = result.getSolverBenchmark();
TerminationConfig originalTerminationConfig = solverBenchmark.getSolverConfig().getTerminationConfig();
TerminationConfig tmpTerminationConfig = originalTerminationConfig.clone();
tmpTerminationConfig.shortenMaximumTimeMillisSpendTotal(timeLeft);
solverBenchmark.getSolverConfig().setTerminationConfig(tmpTerminationConfig);
Solver solver = solverBenchmark.getSolverConfig().buildSolver();
solver.setPlanningProblem(readPlanningProblem());
solver.solve();
solverBenchmark.getSolverConfig().setTerminationConfig(originalTerminationConfig);
long timeSpend = System.currentTimeMillis() - startingTimeMillis;
timeLeft = warmUpTimeMillisSpend - timeSpend;
if (timeLeft <= 0L) {
return timeLeft;
}
}
return timeLeft;
}
public Solution readPlanningProblem() {
return problemIO.read(inputSolutionFile);
}
private void writeSolution(PlannerBenchmarkResult result, Solution outputSolution) {
String solverBenchmarkName = result.getSolverBenchmark().getName()
.replaceAll(" ", "_").replaceAll("[^\\w\\d_\\-]", "");
String filename = name + "_" + solverBenchmarkName + "." + problemIO.getFileExtension();
File outputSolutionFile = new File(outputSolutionFilesDirectory, filename);
problemIO.write(outputSolution, outputSolutionFile);
}
public void benchmarkingEnded() {
determineWinningResult();
determineWinningResultScoreDifference();
}
private void determineWinningResult() {
winningPlannerBenchmarkResult = null;
for (PlannerBenchmarkResult result : plannerBenchmarkResultList) {
if (winningPlannerBenchmarkResult == null
|| result.getScore().compareTo(winningPlannerBenchmarkResult.getScore()) > 0) {
winningPlannerBenchmarkResult = result;
}
}
}
private void determineWinningResultScoreDifference() {
for (PlannerBenchmarkResult result : plannerBenchmarkResultList) {
result.setWinningScoreDifference(result.getScore().subtract(winningPlannerBenchmarkResult.getScore()));
}
}
@Override
public boolean equals(Object o) {
if (this == o) {
return true;
} else if (o instanceof ProblemBenchmark) {
ProblemBenchmark other = (ProblemBenchmark) o;
return inputSolutionFile.equals(other.getInputSolutionFile());
} else {
return false;
}
}
@Override
public int hashCode() {
return inputSolutionFile.hashCode();
}
}