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OptaPlanner solves planning problems.
This lightweight, embeddable planning engine implements powerful and scalable algorithms
to optimize business resource scheduling and planning.
This module contains the examples which demonstrate how to use it in a normal Java application.
/*
* Copyright 2014 Red Hat, Inc. and/or its affiliates.
*
* 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.optaplanner.examples.cheaptime.solver.move.factory;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import java.util.Random;
import org.optaplanner.core.impl.heuristic.move.Move;
import org.optaplanner.core.impl.heuristic.selector.move.factory.MoveIteratorFactory;
import org.optaplanner.core.impl.score.director.ScoreDirector;
import org.optaplanner.examples.cheaptime.domain.CheapTimeSolution;
import org.optaplanner.examples.cheaptime.domain.Machine;
import org.optaplanner.examples.cheaptime.domain.Task;
import org.optaplanner.examples.cheaptime.domain.TaskAssignment;
import org.optaplanner.examples.cheaptime.solver.move.CheapTimePillarSlideMove;
public class CheapTimePillarSlideMoveIteratorFactory implements MoveIteratorFactory {
@Override
public long getSize(ScoreDirector scoreDirector) {
throw new UnsupportedOperationException();
}
@Override
public Iterator> createOriginalMoveIterator(ScoreDirector scoreDirector) {
throw new UnsupportedOperationException();
}
@Override
public RandomCheapTimePillarSlideMoveIterator createRandomMoveIterator(ScoreDirector scoreDirector,
Random workingRandom) {
CheapTimeSolution cheapTimeSolution = scoreDirector.getWorkingSolution();
Map> positivePillarMap = new LinkedHashMap<>(
cheapTimeSolution.getGlobalPeriodRangeTo());
Map> negativePillarMap = new LinkedHashMap<>(
cheapTimeSolution.getGlobalPeriodRangeTo());
List taskAssignmentList = cheapTimeSolution.getTaskAssignmentList();
int pillarCapacity = (taskAssignmentList.size() * 2 / cheapTimeSolution.getMachineList().size()) + 1;
for (TaskAssignment taskAssignment : taskAssignmentList) {
Machine machine = taskAssignment.getMachine();
Task task = taskAssignment.getTask();
Integer startPeriod = taskAssignment.getStartPeriod();
if (startPeriod != null) {
if (startPeriod < task.getStartPeriodRangeTo() - 1) {
List pillar = positivePillarMap.computeIfAbsent(machine,
k -> new ArrayList<>(pillarCapacity));
pillar.add(taskAssignment);
}
if (startPeriod > task.getStartPeriodRangeFrom()) {
List pillar = negativePillarMap.computeIfAbsent(machine,
k -> new ArrayList<>(pillarCapacity));
pillar.add(taskAssignment);
}
}
}
List> positivePillarList = new ArrayList<>(positivePillarMap.size());
for (List pillar : positivePillarMap.values()) {
if (pillar.size() > 1) {
positivePillarList.add(pillar);
}
}
List> negativePillarList = new ArrayList<>(negativePillarMap.size());
for (List pillar : negativePillarMap.values()) {
if (pillar.size() > 1) {
negativePillarList.add(pillar);
}
}
return new RandomCheapTimePillarSlideMoveIterator(positivePillarList, negativePillarList, workingRandom);
}
public static class RandomCheapTimePillarSlideMoveIterator implements Iterator {
private final List> positivePillarList;
private final List> negativePillarList;
private final Random workingRandom;
private final int totalSize;
public RandomCheapTimePillarSlideMoveIterator(List> positivePillarList,
List> negativePillarList, Random workingRandom) {
this.positivePillarList = positivePillarList;
this.negativePillarList = negativePillarList;
this.workingRandom = workingRandom;
totalSize = positivePillarList.size() + negativePillarList.size();
}
@Override
public boolean hasNext() {
return totalSize > 0;
}
@Override
public CheapTimePillarSlideMove next() {
int listIndex = workingRandom.nextInt(totalSize);
boolean positive = listIndex < positivePillarList.size();
List basePillar = positive ? positivePillarList.get(listIndex)
: negativePillarList.get(listIndex - positivePillarList.size());
int basePillarSize = basePillar.size();
int subPillarSize = workingRandom.nextInt(basePillarSize);
// Random sampling: See http://eyalsch.wordpress.com/2010/04/01/random-sample/
// Used Swapping instead of Floyd because subPillarSize is large, to avoid hashCode() hit
TaskAssignment[] sandboxPillar = basePillar.toArray(new TaskAssignment[0]); // Clone to avoid changing basePillar
List subPillar = new ArrayList<>(subPillarSize);
int minimumAbsDiff = Integer.MAX_VALUE;
for (int i = 0; i < subPillarSize; i++) {
int index = i + workingRandom.nextInt(basePillarSize - i);
TaskAssignment taskAssignment = sandboxPillar[index];
Task task = taskAssignment.getTask();
int absDiff = positive ? task.getStartPeriodRangeTo() - 1 - taskAssignment.getStartPeriod()
: taskAssignment.getStartPeriod() - task.getStartPeriodRangeFrom();
if (absDiff < minimumAbsDiff) {
minimumAbsDiff = absDiff;
}
subPillar.add(taskAssignment);
sandboxPillar[index] = sandboxPillar[i];
}
int startPeriodDiff = 1 + workingRandom.nextInt(minimumAbsDiff);
if (!positive) {
startPeriodDiff = -startPeriodDiff;
}
return new CheapTimePillarSlideMove(subPillar, startPeriodDiff);
}
@Override
public void remove() {
throw new UnsupportedOperationException("The optional operation remove() is not supported.");
}
}
}