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org.chocosolver.samples.nsp.NurseScheduling Maven / Gradle / Ivy
/**
* Copyright (c) 2015, Ecole des Mines de Nantes
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* 3. All advertising materials mentioning features or use of this software
* must display the following acknowledgement:
* This product includes software developed by the .
* 4. Neither the name of the nor the
* names of its contributors may be used to endorse or promote products
* derived from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY ''AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL BE LIABLE FOR ANY
* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/*
* Created by IntelliJ IDEA.
* User: sofdem - sophie.demassey{at}emn.fr
* Date: Jul 27, 2010 - 1:45:04 PM
*/
package org.chocosolver.samples.nsp;
import org.chocosolver.solver.Solver;
import org.chocosolver.solver.search.loop.monitors.SearchMonitorFactory;
import org.chocosolver.solver.search.strategy.IntStrategyFactory;
import org.chocosolver.solver.search.strategy.strategy.AbstractStrategy;
import org.chocosolver.solver.variables.IntVar;
import org.chocosolver.solver.variables.Variable;
import org.chocosolver.util.tools.ArrayUtils;
import java.io.BufferedWriter;
import java.io.FileWriter;
import java.io.IOException;
/**
* @author Sophie Demassey
*/
public class NurseScheduling {
enum BranchingStrategy {
/*IMPACT {
AbstractStrategy getGoal(Solver s, IntVar[] vars) {
return new ImpactBasedBranching(s, vars);
}
},*/
INC_DOMWDEG {
AbstractStrategy getGoal(Solver s, IntVar[] vars) {
return IntStrategyFactory.domOverWDeg(vars, System.currentTimeMillis());
}
},
FORCE_INPUT {
AbstractStrategy getGoal(Solver s, IntVar[] vars) {
return IntStrategyFactory.minDom_LB(cast(s.getVars()));
}
},
FORCE_DOMWDEG {
AbstractStrategy getGoal(Solver s, IntVar[] vars) {
return IntStrategyFactory.domOverWDeg(cast(s.getVars()), System.currentTimeMillis());
}
},
/*DOMWDEG {
AbstractStrategy getGoal(Solver s, IntVar[] vars) {
return StrategyFactory.domWDeg(s, vars, new IncreasingDomain());
}
},*/
MIN_DOM {
AbstractStrategy getGoal(Solver s, IntVar[] vars) {
return IntStrategyFactory.minDom_LB(vars);
}
},
/*LEX {
AbstractStrategy getGoal(Solver s, IntVar[] vars) {
return StrategyFactory.lexicographic(s, vars);
}
},*/
RAND {
AbstractStrategy getGoal(Solver s, IntVar[] vars) {
return IntStrategyFactory.random_bound(vars, 0);
}
};
// DOMDDEG { AbstractIntBranchingStrategy getGoal(Solver s, IntVar[] vars) { return BranchingFactory.domDDeg(s, vars, new IncreasingDomain()); }},
AbstractStrategy getGoal(Solver s, IntVar[] vars) {
return null;
}
private static IntVar[] cast(Variable[] vars) {
IntVar[] ivars = new IntVar[vars.length];
for (int i = 0; i < ivars.length; i++) {
ivars[i] = (IntVar) vars[i];
}
return ivars;
}
}
// private AbstractStrategy buildStrategy(Solver solver, IntVar[][] shifts, CostRegular[][] cregs) {
// int[] days = new int[shifts.length * shifts[0].length];
// IntVar[] flatten = new IntVar[shifts.length * shifts[0].length];
// for (int e = 0, k = 0; e < shifts.length; e++) {
// for (int d = 0; d < shifts[e].length; d++, k++) {
// days[k] = d;
// flatten[k] = shifts[e][d];
// }
// }
// IMetric shift2day = new Map(flatten, days);
//
// final THashMap regmap = new THashMap();
// int act = 0; // day
// for (int e = 0; e < shifts.length; e++) {
// for (int d = 0; d < shifts[e].length; d++) {
// regmap.put(shifts[e][d], cregs[e][act]);
// }
// }
//
// IMetric shift2reg = new IMetric() {
// @Override
// public int eval(IntVar var) {
// return regmap.get(var).getMetric("CR_COST").eval(var);
// }
// };
//
// AbstractSorter seq = new Seq(
// new Incr(shift2day),
// new Incr(shift2reg)
// );
// return StrategyVarValAssign.dyn(flatten, seq,
// ValidatorFactory.instanciated, solver.getEnvironment());
// }
public static void runOne(NSData data) {
NSCPModelConstrained.ConstraintOptions basisOptions = NSCPModelConstrained.ConstraintOptions.BASIC;
// NSCPModelConstrained.ConstraintOptions patternOptions = NSCPModelConstrained.ConstraintOptions.WITH_REG;
NSCPModelConstrained.ConstraintOptions patternOptions = NSCPModelConstrained.ConstraintOptions.WITH_MCR;
BranchingStrategy strategy = BranchingStrategy.FORCE_DOMWDEG;
Solver solver = new Solver();
NurseSchedulingProblem m = new NSCPModelConstrained(data, basisOptions, patternOptions, solver);
SearchMonitorFactory.limitTime(solver, 180000);
IntVar[] vars = ArrayUtils.flatten(ArrayUtils.transpose(m.getShifts()));
solver.set(strategy.getGoal(solver, vars));
if (Boolean.TRUE == solver.findSolution()) {
m.printSolution(solver);
NSChecker checker = new NSChecker(data);
if (checker.checkSolution(m.getSolution(solver)))
System.out.println("Solution checked.");
}
String content =
solver.getMeasures().getTimeCount() + " ms,\t " + solver.getMeasures().getNodeCount() + " nodes,\t "
+ solver.getMeasures().getBackTrackCount() + " bks,\t "
+ strategy.name() + "\t " + patternOptions.name() + "\t "
+ m.getDescription() + "\n";
System.out.println(content);
}
public static void runTwo(NSData data) {
NSCPModelConstrained.ConstraintOptions basisOptions = NSCPModelConstrained.ConstraintOptions.REDUNDANT;
// NSCPModelConstrained.ConstraintOptions patternOptions = NSCPModelConstrained.ConstraintOptions.WITH_MCRW;
// NSCPModelConstrained.ConstraintOptions patternOptions = NSCPModelConstrained.ConstraintOptions.WITH_REG;
NSCPModelConstrained.ConstraintOptions patternOptions = NSCPModelConstrained.ConstraintOptions.WITH_MCR;
BranchingStrategy strategy = BranchingStrategy.FORCE_DOMWDEG;
Solver solver = new Solver();
NurseSchedulingProblem m = new NSCPModelConstrained(data, basisOptions, patternOptions, solver);
IntVar[] vars = ArrayUtils.flatten(ArrayUtils.transpose(m.getShifts()));
solver.set(strategy.getGoal(solver, vars));
System.out.printf("%s\n", solver.toString());
if (Boolean.TRUE == solver.findSolution()) {
NSChecker checker = new NSChecker(data);
if (checker.checkSolution(m.getSolution(solver)))
System.out.println("Solution checked.");
}
}
public static void runOne(NSData data, BranchingStrategy strategy, NSCPModelConstrained.ConstraintOptions basisOptions, NSCPModelConstrained.ConstraintOptions patternOptions) {
System.out.println(strategy.name() + "\t " + patternOptions.name() + "\t " + basisOptions.name());
Solver solver = new Solver();
NurseSchedulingProblem m = new NSCPModelConstrained(data, basisOptions, patternOptions, solver);
SearchMonitorFactory.limitTime(solver, 180000);
IntVar[] vars = ArrayUtils.flatten(ArrayUtils.transpose(m.getShifts()));
solver.set(strategy.getGoal(solver, vars));
String solved = "0";
if (Boolean.TRUE == solver.findSolution()) {
m.printSolution(solver);
NSChecker checker = new NSChecker(data);
if (checker.checkSolution(m.getSolution(solver)))
System.out.println("Solution checked.");
solved = "1";
}
String content =
solved + ",\t" + solver.getMeasures().getTimeCount() + " ms,\t "
+ solver.getMeasures().getNodeCount() + " nodes,\t "
+ solver.getMeasures().getBackTrackCount() + " bks,\t "
+ strategy.name() + "\t " + patternOptions.name() + "\t " + basisOptions.name() + "\t "
+ m.getDescription() + "\n";
String contentCSV =
solved + "," + solver.getMeasures().getTimeCount() + ","
+ solver.getMeasures().getNodeCount() + ","
+ solver.getMeasures().getBackTrackCount() + ","
+ strategy.name() + "," + patternOptions.name() + "," + basisOptions.name() + ","
+ m.getDescription() + "\n";
System.out.println(content);
BufferedWriter writer = null;
try {
writer = new BufferedWriter(new FileWriter("out.txt", true));
writer.write(contentCSV);
} catch (IOException ex) {
ex.printStackTrace();
} finally {
try {
if (writer != null) {
writer.flush();
writer.close();
}
} catch (IOException ex) {
ex.printStackTrace();
}
}
}
public static void runAll(NSData data) {
NSCPModelConstrained.ConstraintOptions basisOptions = NSCPModelConstrained.ConstraintOptions.RED_EQUITY;
//NSCPModelConstrained.ConstraintOptions patternOptions = NSCPModelConstrained.ConstraintOptions.WITH_MCRW;
for (BranchingStrategy strategy : BranchingStrategy.values())
for (NSCPModelConstrained.ConstraintOptions patternOptions : NSCPModelConstrained.ConstraintOptions.values())
if (patternOptions.isPatternOption()) {
NurseScheduling.runOne(data, strategy, basisOptions, patternOptions);
}
}
public static void testDefault() {
NSData data = NSData.makeDefaultInstance();
System.out.println("run default instance");
runTwo(data);
}
public static void testLapegue(int numInstance) {
NSParser.read(numInstance);
NSData data = NSData.makeInstanceNSP();
System.out.println("run instance number " + numInstance);
runTwo(data);
}
public static void main(String[] args) {
testDefault();
// testLapegue(5);
}
}
