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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 2010 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.core.localsearch.decider.forager;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.List;
import org.drools.planner.core.localsearch.LocalSearchSolverPhaseScope;
import org.drools.planner.core.localsearch.LocalSearchStepScope;
import org.drools.planner.core.localsearch.decider.MoveScope;
import org.drools.planner.core.localsearch.decider.acceptor.Acceptor;
import org.drools.planner.core.localsearch.decider.deciderscorecomparator.DeciderScoreComparatorFactory;
import org.drools.planner.core.move.Move;
import org.drools.planner.core.score.Score;
/**
* An AcceptedForager is a Forager which forages accepted moves and ignores unaccepted moves.
* @see Forager
* @see Acceptor
*/
public class AcceptedForager extends AbstractForager {
protected DeciderScoreComparatorFactory deciderScoreComparatorFactory;
// final to allow better hotspot optimization. TODO prove that it indeed makes a difference
protected final PickEarlyType pickEarlyType;
protected final int minimalAcceptedSelection;
protected Comparator scoreComparator;
protected AcceptedMoveScopeComparator acceptedMoveScopeComparator;
protected int selectedCount;
protected List acceptedList;
protected List maxScoreAcceptedList;
protected Score maxScore;
protected MoveScope earlyPickedMoveScope;
public AcceptedForager(PickEarlyType pickEarlyType, int minimalAcceptedSelection) {
this.pickEarlyType = pickEarlyType;
this.minimalAcceptedSelection = minimalAcceptedSelection;
}
public void setDeciderScoreComparatorFactory(DeciderScoreComparatorFactory deciderScoreComparator) {
this.deciderScoreComparatorFactory = deciderScoreComparator;
}
// ************************************************************************
// Worker methods
// ************************************************************************
@Override
public void phaseStarted(LocalSearchSolverPhaseScope localSearchSolverPhaseScope) {
deciderScoreComparatorFactory.phaseStarted(localSearchSolverPhaseScope);
}
@Override
public void beforeDeciding(LocalSearchStepScope localSearchStepScope) {
deciderScoreComparatorFactory.beforeDeciding(localSearchStepScope);
scoreComparator = deciderScoreComparatorFactory.createDeciderScoreComparator();
acceptedMoveScopeComparator = new AcceptedMoveScopeComparator(scoreComparator);
selectedCount = 0;
acceptedList = new ArrayList(1024); // TODO use size of moveList in decider
maxScoreAcceptedList = new ArrayList(1024); // TODO use size of moveList in decider
maxScore = localSearchStepScope.getSolverPhaseScope().getScoreDefinition().getPerfectMinimumScore();
earlyPickedMoveScope = null;
}
public void addMove(MoveScope moveScope) {
selectedCount++;
if (moveScope.getAccepted()) {
checkPickEarly(moveScope);
addMoveScopeToAcceptedList(moveScope);
}
}
protected void checkPickEarly(MoveScope moveScope) {
switch (pickEarlyType) {
case NEVER:
break;
case FIRST_BEST_SCORE_IMPROVING:
Score bestScore = moveScope.getLocalSearchStepScope().getSolverPhaseScope().getBestScore();
if (scoreComparator.compare(moveScope.getScore(), bestScore) > 0) {
earlyPickedMoveScope = moveScope;
}
break;
case FIRST_LAST_STEP_SCORE_IMPROVING:
Score lastStepScore = moveScope.getLocalSearchStepScope().getSolverPhaseScope()
.getLastCompletedStepScope().getScore();
if (scoreComparator.compare(moveScope.getScore(), lastStepScore) > 0) {
earlyPickedMoveScope = moveScope;
}
break;
default:
throw new IllegalStateException("The pickEarlyType (" + pickEarlyType + ") is not implemented");
}
}
protected void addMoveScopeToAcceptedList(MoveScope moveScope) {
acceptedList.add(moveScope);
if (scoreComparator.compare(moveScope.getScore(), maxScore) > 0) {
maxScore = moveScope.getScore();
maxScoreAcceptedList.clear();
maxScoreAcceptedList.add(moveScope);
} else if (moveScope.getScore().equals(maxScore)) {
maxScoreAcceptedList.add(moveScope);
}
}
public boolean isQuitEarly() {
return earlyPickedMoveScope != null || acceptedList.size() >= minimalAcceptedSelection;
}
public MoveScope pickMove(LocalSearchStepScope localSearchStepScope) {
if (earlyPickedMoveScope != null) {
return earlyPickedMoveScope;
} else {
return pickMaxScoreMoveScopeFromAcceptedList(localSearchStepScope);
}
}
protected MoveScope pickMaxScoreMoveScopeFromAcceptedList(LocalSearchStepScope localSearchStepScope) {
if (maxScoreAcceptedList.isEmpty()) {
return null;
}
if (maxScoreAcceptedList.size() == 1) {
return maxScoreAcceptedList.get(0);
}
int randomIndex = localSearchStepScope.getWorkingRandom().nextInt(maxScoreAcceptedList.size());
return maxScoreAcceptedList.get(randomIndex);
}
public int getAcceptedMovesSize() {
return acceptedList.size();
}
public List getTopList(int topSize) {
List sortedAcceptedList = new ArrayList(acceptedList);
Collections.sort(sortedAcceptedList, acceptedMoveScopeComparator);
int size = sortedAcceptedList.size();
List topList = new ArrayList(Math.min(topSize, size));
List subAcceptedList = sortedAcceptedList.subList(Math.max(0, size - topSize), size);
for (MoveScope moveScope : subAcceptedList) {
topList.add(moveScope.getMove());
}
return topList;
}
@Override
public void stepTaken(LocalSearchStepScope localSearchStepScope) {
deciderScoreComparatorFactory.stepTaken(localSearchStepScope);
}
@Override
public void phaseEnded(LocalSearchSolverPhaseScope localSearchSolverPhaseScope) {
deciderScoreComparatorFactory.phaseEnded(localSearchSolverPhaseScope);
}
}