Files
ortools-clone/examples/com/google/ortools/samples/SetCoveringDeployment.java
2018-02-19 15:21:05 +01:00

161 lines
4.4 KiB
Java

// Copyright 2011 Hakan Kjellerstrand hakank@gmail.com
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package com.google.ortools.samples;
import java.io.*;
import java.util.*;
import java.text.*;
import com.google.ortools.constraintsolver.DecisionBuilder;
import com.google.ortools.constraintsolver.IntVar;
import com.google.ortools.constraintsolver.Solver;
import com.google.ortools.constraintsolver.OptimizeVar;
public class SetCoveringDeployment {
static {
System.loadLibrary("jniortools");
}
/**
*
* Solves a set covering deployment problem.
* See http://www.hakank.org/google_or_tools/set_covering_deployment.py
*
*/
private static void solve() {
Solver solver = new Solver("SetCoveringDeployment");
//
// data
//
// From http://mathworld.wolfram.com/SetCoveringDeployment.html
String[] countries = {"Alexandria",
"Asia Minor",
"Britain",
"Byzantium",
"Gaul",
"Iberia",
"Rome",
"Tunis"};
int n = countries.length;
// the incidence matrix (neighbours)
int[][] mat = {{0, 1, 0, 1, 0, 0, 1, 1},
{1, 0, 0, 1, 0, 0, 0, 0},
{0, 0, 0, 0, 1, 1, 0, 0},
{1, 1, 0, 0, 0, 0, 1, 0},
{0, 0, 1, 0, 0, 1, 1, 0},
{0, 0, 1, 0, 1, 0, 1, 1},
{1, 0, 0, 1, 1, 1, 0, 1},
{1, 0, 0, 0, 0, 1, 1, 0}};
//
// variables
//
// First army
IntVar[] x = solver.makeIntVarArray(n, 0, 1, "x");
// Second (reserve) army
IntVar[] y = solver.makeIntVarArray(n, 0, 1, "y");
// total number of armies
IntVar num_armies = solver.makeSum(solver.makeSum(x),
solver.makeSum(y)).var();
//
// constraints
//
//
// Constraint 1: There is always an army in a city
// (+ maybe a backup)
// Or rather: Is there a backup, there
// must be an an army
//
for(int i = 0; i < n; i++) {
solver.addConstraint(solver.makeGreaterOrEqual(x[i], y[i]));
}
//
// Constraint 2: There should always be an backup
// army near every city
//
for(int i = 0; i < n; i++) {
ArrayList<IntVar> count_neighbours = new ArrayList<IntVar>();
for(int j = 0; j < n; j++) {
if (mat[i][j] == 1) {
count_neighbours.add(y[j]);
}
}
solver.addConstraint(
solver.makeGreaterOrEqual(
solver.makeSum(x[i],
solver.makeSum(
count_neighbours.toArray(new IntVar[1])).var()), 1));
}
//
// objective
//
OptimizeVar objective = solver.makeMinimize(num_armies, 1);
//
// search
//
DecisionBuilder db = solver.makePhase(x,
solver.INT_VAR_DEFAULT,
solver.INT_VALUE_DEFAULT);
solver.newSearch(db, objective);
//
// output
//
while (solver.nextSolution()) {
System.out.println("num_armies: " + num_armies.value());
for(int i = 0; i < n; i++) {
if (x[i].value() == 1) {
System.out.print("Army: " + countries[i] + " ");
}
if (y[i].value() == 1) {
System.out.println("Reserve army: " + countries[i]);
}
}
}
solver.endSearch();
// Statistics
System.out.println();
System.out.println("Solutions: " + solver.solutions());
System.out.println("Failures: " + solver.failures());
System.out.println("Branches: " + solver.branches());
System.out.println("Wall time: " + solver.wallTime() + "ms");
}
public static void main(String[] args) throws Exception {
SetCoveringDeployment.solve();
}
}