// Copyright 2010-2025 Google LLC // 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. // Minimal example to clone a model. // [START program] package com.google.ortools.linearsolver.samples; // [START import] import com.google.ortools.Loader; import com.google.ortools.modelbuilder.LinearConstraint; import com.google.ortools.modelbuilder.LinearExpr; import com.google.ortools.modelbuilder.ModelBuilder; import com.google.ortools.modelbuilder.ModelSolver; import com.google.ortools.modelbuilder.SolveStatus; import com.google.ortools.modelbuilder.Variable; // [END import] /** Minimal Mixed Integer Programming example to showcase cloning a model. */ public final class CloneModelMb { public static void main(String[] args) { Loader.loadNativeLibraries(); // [START model] // Create the linear model. ModelBuilder model = new ModelBuilder(); // [END model] // [START variables] double infinity = java.lang.Double.POSITIVE_INFINITY; // x and y are integer non-negative variables. Variable x = model.newIntVar(0.0, infinity, "x"); Variable y = model.newIntVar(0.0, infinity, "y"); // [END variables] // [START constraints] // x + 7 * y <= 17.5. LinearConstraint unusedC1 = model.addLessOrEqual(LinearExpr.newBuilder().add(x).addTerm(y, 7), 17.5).withName("c0"); // x <= 3.5. LinearConstraint c2 = model.addLessOrEqual(x, 3.5).withName("c1"); // [END constraints] // [START objective] // Maximize x + 10 * y. model.maximize(LinearExpr.newBuilder().add(x).addTerm(y, 10.0)); // [END objective] // [Start clone] // Clone the model. System.out.println("Cloning the model"); ModelBuilder modelCopy = model.getClone(); Variable xCopy = modelCopy.varFromIndex(x.getIndex()); Variable yCopy = modelCopy.varFromIndex(y.getIndex()); Variable zCopy = modelCopy.newBoolVar("z"); LinearConstraint c2Copy = modelCopy.constraintFromIndex(c2.getIndex()); // Add a new constraint. LinearConstraint unusedC3Copy = modelCopy.addGreaterOrEqual(xCopy, 1); // Modify a constraint. c2Copy.addTerm(zCopy, 2.0); System.out.println("Number of constraints in the original model = " + model.numConstraints()); System.out.println("Number of constraints in the cloned model = " + modelCopy.numConstraints()); // [END clone] // [START solver] // Create the solver with the CP-SAT backend and check it is supported. ModelSolver solver = new ModelSolver("sat"); if (!solver.solverIsSupported()) { return; } // [END solver] // [START solve] final SolveStatus status = solver.solve(modelCopy); // [END solve] // [START print_solution] if (status == SolveStatus.OPTIMAL) { System.out.println("Solution:"); System.out.println("Objective value = " + solver.getObjectiveValue()); System.out.println("x = " + solver.getValue(xCopy)); System.out.println("y = " + solver.getValue(yCopy)); System.out.println("z = " + solver.getValue(zCopy)); } else { System.err.println("The problem does not have an optimal solution!"); } // [END print_solution] // [START advanced] System.out.println("\nAdvanced usage:"); System.out.println("Problem solved in " + solver.getWallTime() + " seconds"); // [END advanced] } private CloneModelMb() {} } // [END program]