001 package net.sf.cpsolver.exam.heuristics; 002 003 import java.text.DecimalFormat; 004 import java.util.ArrayList; 005 import java.util.Collection; 006 import java.util.List; 007 import java.util.Map; 008 009 import net.sf.cpsolver.exam.model.Exam; 010 import net.sf.cpsolver.exam.model.ExamPlacement; 011 import net.sf.cpsolver.exam.neighbours.ExamRandomMove; 012 import net.sf.cpsolver.exam.neighbours.ExamRoomMove; 013 import net.sf.cpsolver.exam.neighbours.ExamTimeMove; 014 import net.sf.cpsolver.ifs.heuristics.NeighbourSelection; 015 import net.sf.cpsolver.ifs.model.Neighbour; 016 import net.sf.cpsolver.ifs.solution.Solution; 017 import net.sf.cpsolver.ifs.solution.SolutionListener; 018 import net.sf.cpsolver.ifs.solver.Solver; 019 import net.sf.cpsolver.ifs.util.DataProperties; 020 import net.sf.cpsolver.ifs.util.JProf; 021 import net.sf.cpsolver.ifs.util.Progress; 022 import net.sf.cpsolver.ifs.util.ToolBox; 023 024 import org.apache.log4j.Logger; 025 026 /** 027 * Greate deluge. In each iteration, one of the following three neighbourhoods 028 * is selected first 029 * <ul> 030 * <li>random move ({@link ExamRandomMove}) 031 * <li>period swap ({@link ExamTimeMove}) 032 * <li>room swap ({@link ExamRoomMove}) 033 * </ul> 034 * , then a neighbour is generated and it is accepted if the value of the new 035 * solution is below certain bound. This bound is initialized to the 036 * GreatDeluge.UpperBoundRate × value of the best solution ever found. 037 * After each iteration, the bound is decreased by GreatDeluge.CoolRate (new 038 * bound equals to old bound × GreatDeluge.CoolRate). If the bound gets 039 * bellow GreatDeluge.LowerBoundRate × value of the best solution ever 040 * found, it is changed back to GreatDeluge.UpperBoundRate × value of the 041 * best solution ever found. 042 * 043 * If there was no improvement found between the bounds, the new bounds are 044 * changed to GreatDeluge.UpperBoundRate^2 and GreatDeluge.LowerBoundRate^2, 045 * GreatDeluge.UpperBoundRate^3 and GreatDeluge.LowerBoundRate^3, etc. till 046 * there is an improvement found. <br> 047 * <br> 048 * 049 * @version ExamTT 1.2 (Examination Timetabling)<br> 050 * Copyright (C) 2008 - 2010 Tomas Muller<br> 051 * <a href="mailto:muller@unitime.org">muller@unitime.org</a><br> 052 * <a href="http://muller.unitime.org">http://muller.unitime.org</a><br> 053 * <br> 054 * This library is free software; you can redistribute it and/or modify 055 * it under the terms of the GNU Lesser General Public License as 056 * published by the Free Software Foundation; either version 3 of the 057 * License, or (at your option) any later version. <br> 058 * <br> 059 * This library is distributed in the hope that it will be useful, but 060 * WITHOUT ANY WARRANTY; without even the implied warranty of 061 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU 062 * Lesser General Public License for more details. <br> 063 * <br> 064 * You should have received a copy of the GNU Lesser General Public 065 * License along with this library; if not see 066 * <a href='http://www.gnu.org/licenses/'>http://www.gnu.org/licenses/</a>. 067 */ 068 public class ExamGreatDeluge implements NeighbourSelection<Exam, ExamPlacement>, SolutionListener<Exam, ExamPlacement> { 069 private static Logger sLog = Logger.getLogger(ExamGreatDeluge.class); 070 private static DecimalFormat sDF2 = new DecimalFormat("0.00"); 071 private static DecimalFormat sDF5 = new DecimalFormat("0.00000"); 072 private double iBound = 0.0; 073 private double iCoolRate = 0.99999995; 074 private long iIter; 075 private double iUpperBound; 076 private double iUpperBoundRate = 1.05; 077 private double iLowerBoundRate = 0.95; 078 private int iMoves = 0; 079 private int iAcceptedMoves = 0; 080 private int iNrIdle = 0; 081 private long iT0 = -1; 082 private long iLastImprovingIter = 0; 083 private double iBestValue = 0; 084 private Progress iProgress = null; 085 086 private List<NeighbourSelection<Exam, ExamPlacement>> iNeighbours = null; 087 088 /** 089 * Constructor. Following problem properties are considered: 090 * <ul> 091 * <li>GreatDeluge.CoolRate ... bound cooling rate (default 0.99999995) 092 * <li>GreatDeluge.UpperBoundRate ... bound upper bound relative to best 093 * solution ever found (default 1.05) 094 * <li>GreatDeluge.LowerBoundRate ... bound lower bound relative to best 095 * solution ever found (default 0.95) 096 * </ul> 097 * 098 * @param properties 099 * problem properties 100 */ 101 @SuppressWarnings("unchecked") 102 public ExamGreatDeluge(DataProperties properties) { 103 iCoolRate = properties.getPropertyDouble("GreatDeluge.CoolRate", iCoolRate); 104 iUpperBoundRate = properties.getPropertyDouble("GreatDeluge.UpperBoundRate", iUpperBoundRate); 105 iLowerBoundRate = properties.getPropertyDouble("GreatDeluge.LowerBoundRate", iLowerBoundRate); 106 String neighbours = properties.getProperty("GreatDeluge.Neighbours", 107 ExamRandomMove.class.getName() + ";" + 108 ExamRoomMove.class.getName() + ";" + 109 ExamTimeMove.class.getName()); 110 neighbours += ";" + properties.getProperty("GreatDeluge.AdditionalNeighbours", ""); 111 iNeighbours = new ArrayList<NeighbourSelection<Exam,ExamPlacement>>(); 112 for (String neighbour: neighbours.split("\\;")) { 113 if (neighbour == null || neighbour.isEmpty()) continue; 114 try { 115 Class<NeighbourSelection<Exam, ExamPlacement>> clazz = (Class<NeighbourSelection<Exam, ExamPlacement>>)Class.forName(neighbour); 116 iNeighbours.add(clazz.getConstructor(DataProperties.class).newInstance(properties)); 117 } catch (Exception e) { 118 sLog.error("Unable to use " + neighbour + ": " + e.getMessage()); 119 } 120 } 121 } 122 123 /** Initialization */ 124 @Override 125 public void init(Solver<Exam, ExamPlacement> solver) { 126 iIter = -1; 127 solver.currentSolution().addSolutionListener(this); 128 for (NeighbourSelection<Exam, ExamPlacement> neighbour: iNeighbours) 129 neighbour.init(solver); 130 solver.setUpdateProgress(false); 131 iProgress = Progress.getInstance(solver.currentSolution().getModel()); 132 } 133 134 /** Print some information */ 135 protected void info(Solution<Exam, ExamPlacement> solution) { 136 sLog.info("Iter=" + iIter / 1000 + "k, NonImpIter=" + sDF2.format((iIter - iLastImprovingIter) / 1000.0) 137 + "k, Speed=" + sDF2.format(1000.0 * iIter / (JProf.currentTimeMillis() - iT0)) + " it/s"); 138 sLog.info("Bound is " + sDF2.format(iBound) + ", " + "best value is " + sDF2.format(solution.getBestValue()) 139 + " (" + sDF2.format(100.0 * iBound / solution.getBestValue()) + "%), " + "current value is " 140 + sDF2.format(solution.getModel().getTotalValue()) + " (" 141 + sDF2.format(100.0 * iBound / solution.getModel().getTotalValue()) + "%), " + "#idle=" + iNrIdle 142 + ", " + "Pacc=" + sDF5.format(100.0 * iAcceptedMoves / iMoves) + "%"); 143 iAcceptedMoves = iMoves = 0; 144 } 145 146 /** 147 * Generate neighbour -- select neighbourhood randomly, select neighbour 148 */ 149 public Neighbour<Exam, ExamPlacement> genMove(Solution<Exam, ExamPlacement> solution) { 150 while (true) { 151 incIter(solution); 152 NeighbourSelection<Exam, ExamPlacement> ns = iNeighbours.get(ToolBox.random(iNeighbours.size())); 153 Neighbour<Exam, ExamPlacement> n = ns.selectNeighbour(solution); 154 if (n != null) 155 return n; 156 } 157 } 158 159 /** Accept neighbour */ 160 protected boolean accept(Solution<Exam, ExamPlacement> solution, Neighbour<Exam, ExamPlacement> neighbour) { 161 return (neighbour.value() <= 0 || solution.getModel().getTotalValue() + neighbour.value() <= iBound); 162 } 163 164 /** Increment iteration count, update bound */ 165 protected void incIter(Solution<Exam, ExamPlacement> solution) { 166 if (iIter < 0) { 167 iIter = 0; 168 iLastImprovingIter = 0; 169 iT0 = JProf.currentTimeMillis(); 170 iBound = (solution.getBestValue() > 0.0 ? iUpperBoundRate * solution.getBestValue() : solution 171 .getBestValue() 172 / iUpperBoundRate); 173 iUpperBound = iBound; 174 iNrIdle = 0; 175 iProgress.setPhase("Great deluge [" + (1 + iNrIdle) + "]..."); 176 } else { 177 iIter++; 178 if (solution.getBestValue() >= 0.0) 179 iBound *= iCoolRate; 180 else 181 iBound /= iCoolRate; 182 } 183 if (iIter % 100000 == 0) { 184 info(solution); 185 } 186 double lowerBound = (solution.getBestValue() >= 0.0 ? Math.pow(iLowerBoundRate, 1 + iNrIdle) 187 * solution.getBestValue() : solution.getBestValue() / Math.pow(iLowerBoundRate, 1 + iNrIdle)); 188 if (iBound < lowerBound) { 189 iNrIdle++; 190 sLog.info(" -<[" + iNrIdle + "]>- "); 191 iBound = Math.max(solution.getBestValue() + 2.0, (solution.getBestValue() >= 0.0 ? Math.pow( 192 iUpperBoundRate, iNrIdle) 193 * solution.getBestValue() : solution.getBestValue() / Math.pow(iUpperBoundRate, iNrIdle))); 194 iUpperBound = iBound; 195 iProgress.setPhase("Great deluge [" + (1 + iNrIdle) + "]..."); 196 } 197 iProgress.setProgress(100 - Math.round(100.0 * (iBound - lowerBound) / (iUpperBound - lowerBound))); 198 } 199 200 /** 201 * A neighbour is generated randomly untill an acceptable one is found. 202 */ 203 @Override 204 public Neighbour<Exam, ExamPlacement> selectNeighbour(Solution<Exam, ExamPlacement> solution) { 205 Neighbour<Exam, ExamPlacement> neighbour = null; 206 while ((neighbour = genMove(solution)) != null) { 207 iMoves++; 208 if (accept(solution, neighbour)) { 209 iAcceptedMoves++; 210 break; 211 } 212 } 213 return (neighbour == null ? null : neighbour); 214 } 215 216 /** Update last improving iteration count */ 217 @Override 218 public void bestSaved(Solution<Exam, ExamPlacement> solution) { 219 if (Math.abs(iBestValue - solution.getBestValue()) >= 1.0) { 220 iLastImprovingIter = iIter; 221 iNrIdle = 0; 222 iBestValue = solution.getBestValue(); 223 } 224 } 225 226 @Override 227 public void solutionUpdated(Solution<Exam, ExamPlacement> solution) { 228 } 229 230 @Override 231 public void getInfo(Solution<Exam, ExamPlacement> solution, Map<String, String> info) { 232 } 233 234 @Override 235 public void getInfo(Solution<Exam, ExamPlacement> solution, Map<String, String> info, Collection<Exam> variables) { 236 } 237 238 @Override 239 public void bestCleared(Solution<Exam, ExamPlacement> solution) { 240 } 241 242 @Override 243 public void bestRestored(Solution<Exam, ExamPlacement> solution) { 244 } 245 246 }