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/*******************************************************************************
* Copyright (c) 2010-2017, Andras Szabolcs Nagy and Daniel Varro
* This program and the accompanying materials are made available under the
* terms of the Eclipse Public License v. 2.0 which is available at
* http://www.eclipse.org/legal/epl-v20.html.
*
* SPDX-License-Identifier: EPL-2.0
*******************************************************************************/
package org.eclipse.viatra.dse.api.strategy.impl;
import java.util.Arrays;
import java.util.Collection;
import java.util.Iterator;
import java.util.PriorityQueue;
import org.apache.log4j.Logger;
import org.eclipse.viatra.dse.api.strategy.interfaces.IStrategy;
import org.eclipse.viatra.dse.base.ThreadContext;
import org.eclipse.viatra.dse.objectives.Fitness;
import org.eclipse.viatra.dse.objectives.ObjectiveComparatorHelper;
import org.eclipse.viatra.dse.solutionstore.SolutionStore;
/**
* This exploration strategy eventually explorers the whole design space but goes in the most promising directions
* first, based on the {@link Fitness}.
*
* There are a few parameter to tune such as
* <ul>
* <li>maximum depth</li>
* <li>continue the exploration from a state that satisfies the hard objectives (the default that it will
* backtrack),</li>
* <li>whether to continue the exploration from the newly explored state if it is at least equally good than the
* previous one or only if it is better (default is "at least equally good").</li>
* </ul>
*
* @author Andras Szabolcs Nagy
*
*/
public class BestFirstStrategy implements IStrategy {
private ThreadContext context;
private SolutionStore solutionStore;
private int maxDepth;
private boolean isInterrupted = false;
private boolean backTrackIfSolution = true;
private boolean onlyBetterFirst = false;
private PriorityQueue<TrajectoryWithFitness> trajectoiresToExplore;
private Logger logger = Logger.getLogger(IStrategy.class);
private static class TrajectoryWithFitness {
public Object[] trajectory;
public Fitness fitness;
public TrajectoryWithFitness(Object[] trajectory, Fitness fitness) {
super();
this.trajectory = trajectory;
this.fitness = fitness;
}
@Override
public String toString() {
return Arrays.toString(trajectory) + fitness.toString();
}
}
/**
* Creates a new best-first search algorithm without depth limit.
*/
public BestFirstStrategy() {
this(-1);
}
/**
* Creates a new best-first search algorithm with depth limit.
*
* @param maxDepth
* A negative <code>maxDepth</code> means no depth limit, zero means the checking of the initial state.
*/
public BestFirstStrategy(int maxDepth) {
if (maxDepth < 0) {
this.maxDepth = Integer.MAX_VALUE;
} else {
this.maxDepth = maxDepth;
}
}
public BestFirstStrategy continueIfHardObjectivesFulfilled() {
backTrackIfSolution = false;
return this;
}
public BestFirstStrategy goOnOnlyIfFitnessIsBetter() {
onlyBetterFirst = true;
return this;
}
@Override
public void initStrategy(ThreadContext context) {
this.context = context;
this.solutionStore = context.getGlobalContext().getSolutionStore();
final ObjectiveComparatorHelper objectiveComparatorHelper = context.getObjectiveComparatorHelper();
trajectoiresToExplore = new PriorityQueue<TrajectoryWithFitness>(11,
(o1, o2) -> objectiveComparatorHelper.compare(o2.fitness, o1.fitness));
}
@Override
public void explore() {
final ObjectiveComparatorHelper objectiveComparatorHelper = context.getObjectiveComparatorHelper();
boolean globalConstraintsAreSatisfied = context.checkGlobalConstraints();
if (!globalConstraintsAreSatisfied) {
logger.info("Global contraint is not satisifed in the first state. Terminate.");
return;
}
final Fitness firstFittness = context.calculateFitness();
if (firstFittness.isSatisifiesHardObjectives()) {
context.newSolution();
logger.info("First state is a solution. Terminate.");
return;
}
if (maxDepth == 0) {
return;
}
final Object[] firstTrajectory = context.getTrajectory().toArray(new Object[0]);
TrajectoryWithFitness currentTrajectoryWithFittness = new TrajectoryWithFitness(firstTrajectory, firstFittness);
trajectoiresToExplore.add(currentTrajectoryWithFittness);
mainLoop: while (!isInterrupted) {
if (currentTrajectoryWithFittness == null) {
if (trajectoiresToExplore.isEmpty()) {
logger.debug("State space is fully traversed.");
return;
} else {
currentTrajectoryWithFittness = trajectoiresToExplore.element();
if (logger.isDebugEnabled()) {
logger.debug("New trajectory is chosen: " + currentTrajectoryWithFittness);
}
context.getDesignSpaceManager().executeTrajectoryWithMinimalBacktrackWithoutStateCoding(currentTrajectoryWithFittness.trajectory);
}
}
Collection<Object> activationIds = context.getUntraversedActivationIds();
Iterator<Object> iterator = activationIds.iterator();
while (!isInterrupted && iterator.hasNext()) {
final Object nextActivation = iterator.next();
if (!iterator.hasNext()) {
logger.debug("Last untraversed activation of the state.");
trajectoiresToExplore.remove(currentTrajectoryWithFittness);
}
if (logger.isDebugEnabled()) {
logger.debug("Executing new activation: " + nextActivation);
}
context.executeAcitvationId(nextActivation);
if (context.isCurrentStateAlreadyTraversed()) {
logger.info("The new state is already visited.");
context.backtrack();
} else if (!context.checkGlobalConstraints()) {
logger.debug("Global contraint is not satisifed.");
context.backtrack();
} else {
final Fitness nextFitness = context.calculateFitness();
if (nextFitness.isSatisifiesHardObjectives()) {
solutionStore.newSolution(context);
logger.debug("Found a solution.");
if (backTrackIfSolution) {
context.backtrack();
continue;
}
}
if (context.getDepth() >= maxDepth) {
logger.debug("Reached max depth.");
context.backtrack();
continue;
}
TrajectoryWithFitness nextTrajectoryWithFittness = new TrajectoryWithFitness(
context.getTrajectory().toArray(), nextFitness);
trajectoiresToExplore.add(nextTrajectoryWithFittness);
int compare = objectiveComparatorHelper.compare(currentTrajectoryWithFittness.fitness,
nextTrajectoryWithFittness.fitness);
if (compare < 0) {
logger.debug("Better fitness, moving on: " + nextFitness);
currentTrajectoryWithFittness = nextTrajectoryWithFittness;
continue mainLoop;
} else if (compare == 0) {
if (onlyBetterFirst) {
logger.debug("Equally good fitness, backtrack: " + nextFitness);
context.backtrack();
continue;
} else {
logger.debug("Equally good fitness, moving on: " + nextFitness);
currentTrajectoryWithFittness = nextTrajectoryWithFittness;
continue mainLoop;
}
} else {
logger.debug("Worse fitness.");
currentTrajectoryWithFittness = null;
continue mainLoop;
}
}
}
logger.debug("State is fully traversed.");
trajectoiresToExplore.remove(currentTrajectoryWithFittness);
currentTrajectoryWithFittness = null;
}
logger.info("Interrupted.");
}
@Override
public void interruptStrategy() {
isInterrupted = true;
}
}
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