    001package net.sf.cpsolver.ifs.perturbations;
    002
    003import java.util.Collection;
    004import java.util.Map;
    005
    006import net.sf.cpsolver.ifs.model.Model;
    007import net.sf.cpsolver.ifs.model.Value;
    008import net.sf.cpsolver.ifs.model.Variable;
    009import net.sf.cpsolver.ifs.solution.Solution;
    010import net.sf.cpsolver.ifs.solver.Solver;
    011
    012/**
    013 * Counter of perturbation penalty (minimal perturbation problem). <br>
    014 * <br>
    015 * Many real-life problems are dynamic, with changes in the problem definition
    016 * occurring after a solution to the initial formulation has been reached. A
    017 * minimal perturbation problem incorporates these changes, along with the
    018 * initial solution, as a new problem whose solution must be as close as
    019 * possible to the initial solution. The iterative forward search algorithm is
    020 * also made to solve minimal perturbation problems. <br>
    021 * <br>
    022 * To define the minimal perturbation problem, we will consider an initial
    023 * (original) problem, its solution, a new problem, and some distance function
    024 * which allows us to compare solutions of the initial and the new problem.
    025 * Subsequently we look for a solution of the new problem with minimal distance
    026 * from the initial solution. This distance is expressed by this
    027 * PerturbationCounter
    028 *
    029 * @see Solver
    030 * @see Solution
    031 * @see Variable
    032 *
    033 * @version IFS 1.2 (Iterative Forward Search)<br>
    034 *          Copyright (C) 2006 - 2010 Tomáš Müller<br>
    035 *          <a href="mailto:muller@unitime.org">muller@unitime.org</a><br>
    036 *          <a href="http://muller.unitime.org">http://muller.unitime.org</a><br>
    037 * <br>
    038 *          This library is free software; you can redistribute it and/or modify
    039 *          it under the terms of the GNU Lesser General Public License as
    040 *          published by the Free Software Foundation; either version 3 of the
    041 *          License, or (at your option) any later version. <br>
    042 * <br>
    043 *          This library is distributed in the hope that it will be useful, but
    044 *          WITHOUT ANY WARRANTY; without even the implied warranty of
    045 *          MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
    046 *          Lesser General Public License for more details. <br>
    047 * <br>
    048 *          You should have received a copy of the GNU Lesser General Public
    049 *          License along with this library; if not see
    050 *          <a href='http://www.gnu.org/licenses/'>http://www.gnu.org/licenses/</a>.
    051 */
    052public interface PerturbationsCounter<V extends Variable<V, T>, T extends Value<V, T>> {
    053    /** Initialization */
    054    public void init(Solver<V, T> solver);
    055
    056    /**
    057     * Returns perturbation penalty, i.e., the distance between current solution
    058     * and the solution of the initial problem (see
    059     * {@link Variable#getInitialAssignment()}).
    060     *
    061     * @param model
    062     *            current model
    063     */
    064    public double getPerturbationPenalty(Model<V, T> model);
    065
    066    /**
    067     * Returns perturbation penalty, i.e., the distance between current solution
    068     * and the solution of the initial (only include variables from the given
    069     * set) problem (see {@link Variable#getInitialAssignment()}).
    070     *
    071     * @param model
    072     *            current model
    073     */
    074    public double getPerturbationPenalty(Model<V, T> model, Collection<V> variables);
    075
    076    /**
    077     * Returns perturbation penalty of the solution which become from the
    078     * current solution when given conflicting values are unassigned and the
    079     * selected value is assigned. Since this penalty is used for comparison of
    080     * different candidate values in the value selection criterion, it is fully
    081     * acceptable to just return a difference between current and the altered
    082     * solution (which might be easied for computation that the whole
    083     * perturbation penalty).
    084     *
    085     * @param model
    086     *            current model
    087     * @param selectedValue
    088     *            value to be selected in the next iteration
    089     * @param conflicts
    090     *            conflicting values to be unassigned in the next iteration
    091     */
    092    public double getPerturbationPenalty(Model<V, T> model, T selectedValue, Collection<T> conflicts);
    093
    094    /**
    095     * Some (perturbation) information about the solution might be returned
    096     * here.
    097     *
    098     * @param info
    099     *            resultant info table
    100     * @param model
    101     *            current model
    102     */
    103    public void getInfo(Map<String, String> info, Model<V, T> model);
    104
    105    /**
    106     * Some (perturbation) information about the solution might be returned here
    107     * (only include variables from the given set).
    108     *
    109     * @param info
    110     *            resultant info table
    111     * @param model
    112     *            current model
    113     */
    114    public void getInfo(Map<String, String> info, Model<V, T> model, Collection<V> variables);
    115}