001package net.sf.cpsolver.coursett.criteria;
002
003import java.util.Collection;
004import java.util.HashSet;
005import java.util.Set;
006
007import net.sf.cpsolver.coursett.Constants;
008import net.sf.cpsolver.coursett.constraint.InstructorConstraint;
009import net.sf.cpsolver.coursett.model.Lecture;
010import net.sf.cpsolver.coursett.model.Placement;
011import net.sf.cpsolver.coursett.model.TimetableModel;
012
013import net.sf.cpsolver.ifs.util.DataProperties;
014
015/**
016 * Bact-to-back instructor preferences. This criterion counts cases when an instructor
017 * has to teach two classes in two rooms that are too far a part. This objective
018 * is counter by the {@link InstructorConstraint}
019 * (see {@link InstructorConstraint#getDistancePreference(Placement, Placement)}).
020 * <br>
021 * 
022 * @version CourseTT 1.2 (University Course Timetabling)<br>
023 *          Copyright (C) 2006 - 2011 Tomáš Müller<br>
024 *          <a href="mailto:muller@unitime.org">muller@unitime.org</a><br>
025 *          <a href="http://muller.unitime.org">http://muller.unitime.org</a><br>
026 * <br>
027 *          This library is free software; you can redistribute it and/or modify
028 *          it under the terms of the GNU Lesser General Public License as
029 *          published by the Free Software Foundation; either version 3 of the
030 *          License, or (at your option) any later version. <br>
031 * <br>
032 *          This library is distributed in the hope that it will be useful, but
033 *          WITHOUT ANY WARRANTY; without even the implied warranty of
034 *          MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
035 *          Lesser General Public License for more details. <br>
036 * <br>
037 *          You should have received a copy of the GNU Lesser General Public
038 *          License along with this library; if not see
039 *          <a href='http://www.gnu.org/licenses/'>http://www.gnu.org/licenses/</a>.
040 */
041public class BackToBackInstructorPreferences extends TimetablingCriterion {
042    
043    public BackToBackInstructorPreferences() {
044        iValueUpdateType = ValueUpdateType.NoUpdate;
045    }
046    
047    @Override
048    public double getWeightDefault(DataProperties config) {
049        return Constants.sPreferenceLevelDiscouraged * config.getPropertyDouble("Comparator.DistanceInstructorPreferenceWeight", 1.0);
050    }
051    
052    @Override
053    public String getPlacementSelectionWeightName() {
054        return "Placement.DistanceInstructorPreferenceWeight";
055    }
056    
057    protected int penalty(Placement value) {
058        int ret = 0;
059        for (InstructorConstraint ic: value.variable().getInstructorConstraints()) {
060            ret += ic.getPreference(value);
061        }
062        return ret;
063    }
064    
065    @Override
066    public double getValue(Placement value, Set<Placement> conflicts) {
067        double ret = penalty(value);
068        if (conflicts != null)
069            for (Placement conflict: conflicts)
070                ret -= penalty(conflict);
071        return ret;
072    }
073
074    @Override
075    public double getValue(Collection<Lecture> variables) {
076        double ret = 0;
077        Set<InstructorConstraint> constraints = new HashSet<InstructorConstraint>();
078        for (Lecture lect: variables) {
079            for (InstructorConstraint ic: lect.getInstructorConstraints()) {
080                if (!constraints.add(ic)) continue;
081                ret += ic.getPreference();
082            }
083        }
084        return ret;
085    }
086    
087    @Override
088    protected double[] computeBounds() {
089        double[] bounds = new double[] { 0.0, 0.0 };
090        for (InstructorConstraint ic: ((TimetableModel)getModel()).getInstructorConstraints())
091            bounds[1] += ic.getWorstPreference();
092        return bounds;
093    }
094    
095    @Override
096    public double[] getBounds(Collection<Lecture> variables) {
097        double[] bounds = new double[] { 0.0, 0.0 };
098        Set<InstructorConstraint> constraints = new HashSet<InstructorConstraint>();
099        for (Lecture lect: variables) {
100            for (InstructorConstraint ic: lect.getInstructorConstraints()) {
101                if (!constraints.add(ic)) continue;
102                bounds[1] += ic.getWorstPreference();
103            }
104        }
105        return bounds;
106    }
107}