109 lines
3.6 KiB
Java
109 lines
3.6 KiB
Java
// Copyright 2010-2024 Google LLC
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// [START program]
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package com.google.ortools.sat.samples;
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// [START import]
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import com.google.ortools.Loader;
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import com.google.ortools.sat.CpModel;
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import com.google.ortools.sat.CpSolver;
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import com.google.ortools.sat.CpSolverSolutionCallback;
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import com.google.ortools.sat.IntVar;
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import com.google.ortools.sat.LinearExpr;
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// [END import]
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/** Cryptarithmetic puzzle. */
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public final class CpIsFunSat {
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// [START solution_printer]
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static class VarArraySolutionPrinter extends CpSolverSolutionCallback {
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public VarArraySolutionPrinter(IntVar[] variables) {
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variableArray = variables;
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}
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@Override
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public void onSolutionCallback() {
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for (IntVar v : variableArray) {
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System.out.printf(" %s = %d", v.getName(), value(v));
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}
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System.out.println();
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solutionCount++;
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}
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public int getSolutionCount() {
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return solutionCount;
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}
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private int solutionCount;
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private final IntVar[] variableArray;
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}
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// [END solution_printer]
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public static void main(String[] args) throws Exception {
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Loader.loadNativeLibraries();
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// Create the model.
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// [START model]
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CpModel model = new CpModel();
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// [END model]
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// [START variables]
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int base = 10;
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IntVar c = model.newIntVar(1, base - 1, "C");
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IntVar p = model.newIntVar(0, base - 1, "P");
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IntVar i = model.newIntVar(1, base - 1, "I");
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IntVar s = model.newIntVar(0, base - 1, "S");
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IntVar f = model.newIntVar(1, base - 1, "F");
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IntVar u = model.newIntVar(0, base - 1, "U");
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IntVar n = model.newIntVar(0, base - 1, "N");
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IntVar t = model.newIntVar(1, base - 1, "T");
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IntVar r = model.newIntVar(0, base - 1, "R");
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IntVar e = model.newIntVar(0, base - 1, "E");
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// We need to group variables in a list to use the constraint AllDifferent.
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IntVar[] letters = new IntVar[] {c, p, i, s, f, u, n, t, r, e};
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// [END variables]
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// Define constraints.
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// [START constraints]
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model.addAllDifferent(letters);
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// CP + IS + FUN = TRUE
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model.addEquality(LinearExpr.weightedSum(new IntVar[] {c, p, i, s, f, u, n, t, r, u, e},
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new long[] {base, 1, base, 1, base * base, base, 1, -base * base * base,
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-base * base, -base, -1}),
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0);
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// [END constraints]
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// Create a solver and solve the model.
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// [START solve]
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CpSolver solver = new CpSolver();
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VarArraySolutionPrinter cb = new VarArraySolutionPrinter(letters);
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// Tell the solver to enumerate all solutions.
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solver.getParameters().setEnumerateAllSolutions(true);
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// And solve.
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solver.solve(model, cb);
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// [END solve]
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// Statistics.
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// [START statistics]
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System.out.println("Statistics");
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System.out.println(" - conflicts : " + solver.numConflicts());
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System.out.println(" - branches : " + solver.numBranches());
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System.out.println(" - wall time : " + solver.wallTime() + " s");
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System.out.println(" - solutions : " + cb.getSolutionCount());
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// [END statistics]
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}
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private CpIsFunSat() {}
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}
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// [END program]
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