001package org.cpsolver.ifs.perturbations;
002
003import java.util.Collection;
004import java.util.Map;
005
006import org.cpsolver.ifs.assignment.Assignment;
007import org.cpsolver.ifs.model.Model;
008import org.cpsolver.ifs.model.Value;
009import org.cpsolver.ifs.model.Variable;
010import org.cpsolver.ifs.solution.Solution;
011import org.cpsolver.ifs.solver.Solver;
012
013
014/**
015 * Counter of perturbation penalty (minimal perturbation problem). <br>
016 * <br>
017 * Many real-life problems are dynamic, with changes in the problem definition
018 * occurring after a solution to the initial formulation has been reached. A
019 * minimal perturbation problem incorporates these changes, along with the
020 * initial solution, as a new problem whose solution must be as close as
021 * possible to the initial solution. The iterative forward search algorithm is
022 * also made to solve minimal perturbation problems. <br>
023 * <br>
024 * To define the minimal perturbation problem, we will consider an initial
025 * (original) problem, its solution, a new problem, and some distance function
026 * which allows us to compare solutions of the initial and the new problem.
027 * Subsequently we look for a solution of the new problem with minimal distance
028 * from the initial solution. This distance is expressed by this
029 * PerturbationCounter
030 * 
031 * @see Solver
032 * @see Solution
033 * @see Variable
034 * 
035 * @version IFS 1.3 (Iterative Forward Search)<br>
036 *          Copyright (C) 2006 - 2014 Tomáš Müller<br>
037 *          <a href="mailto:muller@unitime.org">muller@unitime.org</a><br>
038 *          <a href="http://muller.unitime.org">http://muller.unitime.org</a><br>
039 * <br>
040 *          This library is free software; you can redistribute it and/or modify
041 *          it under the terms of the GNU Lesser General Public License as
042 *          published by the Free Software Foundation; either version 3 of the
043 *          License, or (at your option) any later version. <br>
044 * <br>
045 *          This library is distributed in the hope that it will be useful, but
046 *          WITHOUT ANY WARRANTY; without even the implied warranty of
047 *          MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
048 *          Lesser General Public License for more details. <br>
049 * <br>
050 *          You should have received a copy of the GNU Lesser General Public
051 *          License along with this library; if not see
052 *          <a href='http://www.gnu.org/licenses/'>http://www.gnu.org/licenses/</a>.
053 *
054 * @param <V> Variable
055 * @param <T> Value
056 */
057public interface PerturbationsCounter<V extends Variable<V, T>, T extends Value<V, T>> {
058    /** Initialization 
059     * @param solver current solver
060     **/
061    public void init(Solver<V, T> solver);
062
063    /**
064     * Returns perturbation penalty, i.e., the distance between current solution
065     * and the solution of the initial problem (see
066     * {@link Variable#getInitialAssignment()}).
067     * 
068     * @param assignment current assignment
069     * @param model
070     *            current model
071     * @return penalty 
072     */
073    public double getPerturbationPenalty(Assignment<V, T> assignment, Model<V, T> model);
074
075    /**
076     * Returns perturbation penalty, i.e., the distance between current solution
077     * and the solution of the initial (only include variables from the given
078     * set) problem (see {@link Variable#getInitialAssignment()}).
079     * 
080     * @param assignment current assignment
081     * @param model
082     *            current model
083     * @param variables sub-problem
084     * @return penalty
085     */
086    public double getPerturbationPenalty(Assignment<V, T> assignment, Model<V, T> model, Collection<V> variables);
087
088    /**
089     * Returns perturbation penalty of the solution which become from the
090     * current solution when given conflicting values are unassigned and the
091     * selected value is assigned. Since this penalty is used for comparison of
092     * different candidate values in the value selection criterion, it is fully
093     * acceptable to just return a difference between current and the altered
094     * solution (which might be easied for computation that the whole
095     * perturbation penalty).
096     * 
097     * @param assignment current assignment
098     * @param model
099     *            current model
100     * @param selectedValue
101     *            value to be selected in the next iteration
102     * @param conflicts
103     *            conflicting values to be unassigned in the next iteration
104     * @return penalty
105     */
106    public double getPerturbationPenalty(Assignment<V, T> assignment, Model<V, T> model, T selectedValue, Collection<T> conflicts);
107
108    /**
109     * Some (perturbation) information about the solution might be returned
110     * here.
111     * 
112     * @param assignment current assignment
113     * @param info
114     *            resultant info table
115     * @param model
116     *            current model
117     */
118    public void getInfo(Assignment<V, T> assignment, Model<V, T> model, Map<String, String> info);
119
120    /**
121     * Some (perturbation) information about the solution might be returned here
122     * (only include variables from the given set).
123     * 
124     * @param assignment current assignment
125     * @param info
126     *            resultant info table
127     * @param model
128     *            current model
129     * @param variables sub-problem
130     */
131    public void getInfo(Assignment<V, T> assignment, Model<V, T> model, Map<String, String> info, Collection<V> variables);
132}