Add ModelBuilder.clone() java API + sample
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@@ -36,6 +36,8 @@ code_sample_cc(name = "stigler_diet")
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# Model Builder
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code_sample_java(name = "CloneModelMb")
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code_sample_java(name = "SimpleLpProgramMb")
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code_sample_java(name = "SimpleMipProgramMb")
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101
ortools/linear_solver/samples/CloneModelMb.java
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101
ortools/linear_solver/samples/CloneModelMb.java
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@@ -0,0 +1,101 @@
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// Copyright 2010-2022 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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// Minimal example to call the MIP solver.
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// [START program]
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package com.google.ortools.linearsolver.samples;
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// [START import]
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import com.google.ortools.Loader;
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import com.google.ortools.modelbuilder.LinearConstraint;
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import com.google.ortools.modelbuilder.LinearExpr;
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import com.google.ortools.modelbuilder.ModelBuilder;
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import com.google.ortools.modelbuilder.ModelSolver;
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import com.google.ortools.modelbuilder.SolveStatus;
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import com.google.ortools.modelbuilder.Variable;
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// [END import]
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/** Minimal Mixed Integer Programming example to showcase cloning a model. */
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public final class CloneModelMb {
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public static void main(String[] args) {
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Loader.loadNativeLibraries();
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// [START model]
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// Create the linear model.
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ModelBuilder model = new ModelBuilder();
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// [END model]
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// [START variables]
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double infinity = java.lang.Double.POSITIVE_INFINITY;
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// x and y are integer non-negative variables.
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Variable x = model.newIntVar(0.0, infinity, "x");
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Variable y = model.newIntVar(0.0, infinity, "y");
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// [END variables]
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// [START constraints]
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// x + 7 * y <= 17.5.
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LinearConstraint unusedC1 =
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model.addLessOrEqual(LinearExpr.newBuilder().add(x).addTerm(y, 7), 17.5).withName("c0");
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// x <= 3.5.
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LinearConstraint c2 = model.addLessOrEqual(x, 3.5).withName("c1");
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// [END constraints]
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// [START objective]
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// Maximize x + 10 * y.
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model.maximize(LinearExpr.newBuilder().add(x).addTerm(y, 10.0));
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// [END objective]
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// Deep copy
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System.out.println("Cloning the model");
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ModelBuilder modelCopy = model.clone();
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Variable xCopy = modelCopy.varFromIndex(x.getIndex());
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Variable yCopy = modelCopy.varFromIndex(y.getIndex());
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Variable zCopy = modelCopy.newBoolVar("z");
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LinearConstraint c2Copy = modelCopy.constraintFromIndex(c2.getIndex());
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// Add new constraint.
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LinearConstraint c3Copy = modelCopy.addGreaterOrEqual(xCopy, 1);
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// Modify a constraint.
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c2Copy.addTerm(zCopy, 2.0);
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System.out.println("Number of constraints in the original model = " + model.numConstraints());
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System.out.println("Number of constraints in the cloned model = " + modelCopy.numConstraints());
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// [START solve]
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// Solve with the SCIP MIP solver.
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ModelSolver solver = new ModelSolver("scip");
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final SolveStatus status = solver.solve(modelCopy);
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// [END solve]
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// [START print_solution]
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if (status == SolveStatus.OPTIMAL) {
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System.out.println("Solution:");
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System.out.println("Objective value = " + solver.getObjectiveValue());
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System.out.println("x = " + solver.getValue(xCopy));
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System.out.println("y = " + solver.getValue(yCopy));
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System.out.println("z = " + solver.getValue(zCopy));
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} else {
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System.err.println("The problem does not have an optimal solution!");
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}
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// [END print_solution]
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// [START advanced]
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System.out.println("\nAdvanced usage:");
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System.out.println("Problem solved in " + solver.getWallTime() + " seconds");
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// [END advanced]
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}
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private CloneModelMb() {}
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}
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// [END program]
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