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}