001package net.sf.cpsolver.studentsct.heuristics.selection;
002
003import java.util.Set;
004
005import net.sf.cpsolver.ifs.heuristics.NeighbourSelection;
006import net.sf.cpsolver.ifs.heuristics.RoundRobinNeighbourSelection;
007import net.sf.cpsolver.ifs.model.Neighbour;
008import net.sf.cpsolver.ifs.solution.Solution;
009import net.sf.cpsolver.ifs.solver.Solver;
010import net.sf.cpsolver.ifs.util.DataProperties;
011import net.sf.cpsolver.ifs.util.Progress;
012import net.sf.cpsolver.ifs.util.ToolBox;
013import net.sf.cpsolver.studentsct.model.Enrollment;
014import net.sf.cpsolver.studentsct.model.Request;
015import net.sf.cpsolver.studentsct.model.Student;
016
017/**
018 * Random unassignment of some problematic students. Problematic students are to
019 * be provided by a neighbour selection that was used before this one by
020 * {@link RoundRobinNeighbourSelection}.
021 * 
022 * <br>
023 * <br>
024 * In each step a problematic student is randomly selected with the given
025 * probabilty. Null is returned otherwise (the controll is passed to the next
026 * {@link NeighbourSelection}).
027 * 
028 * <br>
029 * <br>
030 * Parameters: <br>
031 * <table border='1'>
032 * <tr>
033 * <th>Parameter</th>
034 * <th>Type</th>
035 * <th>Comment</th>
036 * </tr>
037 * <tr>
038 * <td>Neighbour.RandomUnassignmentOfProblemStudentProb</td>
039 * <td>{@link Double}</td>
040 * <td>Probability of a random selection of a student from the given set of
041 * problematic students.</td>
042 * </tr>
043 * </table>
044 * <br>
045 * <br>
046 * 
047 * @version StudentSct 1.2 (Student Sectioning)<br>
048 *          Copyright (C) 2007 - 2010 Tomáš Müller<br>
049 *          <a href="mailto:muller@unitime.org">muller@unitime.org</a><br>
050 *          <a href="http://muller.unitime.org">http://muller.unitime.org</a><br>
051 * <br>
052 *          This library is free software; you can redistribute it and/or modify
053 *          it under the terms of the GNU Lesser General Public License as
054 *          published by the Free Software Foundation; either version 3 of the
055 *          License, or (at your option) any later version. <br>
056 * <br>
057 *          This library is distributed in the hope that it will be useful, but
058 *          WITHOUT ANY WARRANTY; without even the implied warranty of
059 *          MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
060 *          Lesser General Public License for more details. <br>
061 * <br>
062 *          You should have received a copy of the GNU Lesser General Public
063 *          License along with this library; if not see
064 *          <a href='http://www.gnu.org/licenses/'>http://www.gnu.org/licenses/</a>.
065 */
066public class RndUnProblStudSelection extends RandomUnassignmentSelection {
067    private ProblemStudentsProvider iProblemStudentsProvider = null;
068    private Set<Student> iProblemStudents = null;
069
070    /**
071     * Constructor
072     * 
073     * @param properties
074     *            configuration
075     * @param psp
076     *            a class that provides the set of problematic students
077     */
078    public RndUnProblStudSelection(DataProperties properties, ProblemStudentsProvider psp) {
079        super(properties);
080        iProblemStudentsProvider = psp;
081        iRandom = properties.getPropertyDouble("Neighbour.RandomUnassignmentOfProblemStudentProb", 0.9);
082    }
083
084    /**
085     * Initialization -- {@link ProblemStudentsProvider#getProblemStudents()} is
086     * called
087     */
088    @Override
089    public void init(Solver<Request, Enrollment> solver) {
090        iProblemStudents = iProblemStudentsProvider.getProblemStudents();
091        Progress.getInstance(solver.currentSolution().getModel()).setPhase(
092                "Random unassignment of problematic students...", 1);
093    }
094
095    /**
096     * With the given probabilty, a problematic student is randomly selected to
097     * be unassigned. Null is returned otherwise.
098     */
099    @Override
100    public Neighbour<Request, Enrollment> selectNeighbour(Solution<Request, Enrollment> solution) {
101        if (!iProblemStudents.isEmpty() && Math.random() < iRandom) {
102            Student student = ToolBox.random(iProblemStudents);
103            iProblemStudents.remove(student);
104            return new UnassignStudentNeighbour(student);
105        }
106        Progress.getInstance(solution.getModel()).incProgress();
107        return null;
108    }
109}