85 lines
3.0 KiB
Java
85 lines
3.0 KiB
Java
// Copyright 2010-2021 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 static java.util.Arrays.stream;
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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.CpSolverStatus;
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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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/** Minimal CP-SAT example to showcase calling the solver. */
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public final class CpSatExample {
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public static void main(String[] args) {
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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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// Create the variables.
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// [START variables]
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int varUpperBound = stream(new int[] {50, 45, 37}).max().getAsInt();
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IntVar x = model.newIntVar(0, varUpperBound, "x");
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IntVar y = model.newIntVar(0, varUpperBound, "y");
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IntVar z = model.newIntVar(0, varUpperBound, "z");
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// [END variables]
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// Create the constraints.
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// [START constraints]
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model.addLessOrEqual(LinearExpr.weightedSum(new IntVar[] {x, y, z}, new long[] {2, 7, 3}), 50);
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model.addLessOrEqual(LinearExpr.weightedSum(new IntVar[] {x, y, z}, new long[] {3, -5, 7}), 45);
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model.addLessOrEqual(LinearExpr.weightedSum(new IntVar[] {x, y, z}, new long[] {5, 2, -6}), 37);
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// [END constraints]
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// [START objective]
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model.maximize(LinearExpr.weightedSum(new IntVar[] {x, y, z}, new long[] {2, 2, 3}));
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// [END objective]
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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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CpSolverStatus status = solver.solve(model);
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// [END solve]
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// [START print_solution]
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if (status == CpSolverStatus.OPTIMAL || status == CpSolverStatus.FEASIBLE) {
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System.out.printf("Maximum of objective function: %f%n", solver.objectiveValue());
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System.out.println("x = " + solver.value(x));
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System.out.println("y = " + solver.value(y));
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System.out.println("z = " + solver.value(z));
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} else {
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System.out.println("No solution found.");
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}
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// [END print_solution]
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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.printf(" conflicts: %d%n", solver.numConflicts());
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System.out.printf(" branches : %d%n", solver.numBranches());
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System.out.printf(" wall time: %f s%n", solver.wallTime());
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// [END statistics]
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}
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private CpSatExample() {}
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}
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// [END program]
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