Add Samples from g3

ortools/linear_solver/samples/linear_programming_example.cc

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+// Copyright 2010-2018 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.
+
+// [START program]
+// [START import]
+#include <iostream>
+#include "ortools/linear_solver/linear_solver.h"
+// [END import]
+
+namespace operations_research {
+void LinearProgrammingExample() {
+  // [START solver]
+  MPSolver solver("LinearExample", MPSolver::GLOP_LINEAR_PROGRAMMING);
+  // [END solver]
+
+  // [START variables]
+  const double infinity = solver.infinity();
+  // x and y are non-negative variables.
+  MPVariable* const x = solver.MakeNumVar(0.0, infinity, "x");
+  MPVariable* const y = solver.MakeNumVar(0.0, infinity, "y");
+  LOG(INFO) << "Number of variables = " << solver.NumVariables();
+  // [END variables]
+
+  // [START constraints]
+  // x + 2*y <= 14.
+  MPConstraint* const c0 = solver.MakeRowConstraint(-infinity, 14.0);
+  c0->SetCoefficient(x, 1);
+  c0->SetCoefficient(y, 2);
+
+  // 3*x - y >= 0.
+  MPConstraint* const c1 = solver.MakeRowConstraint(0.0, infinity);
+  c1->SetCoefficient(x, 3);
+  c1->SetCoefficient(y, -1);
+
+  // x - y <= 2.
+  MPConstraint* const c2 = solver.MakeRowConstraint(-infinity, 2.0);
+  c2->SetCoefficient(x, 1);
+  c2->SetCoefficient(y, -1);
+  LOG(INFO) << "Number of constraints = " << solver.NumConstraints();
+  // [END constraints]
+
+  // [START objective]
+  // Objective function: 3x + 4y.
+  MPObjective* const objective = solver.MutableObjective();
+  objective->SetCoefficient(x, 3);
+  objective->SetCoefficient(y, 4);
+  objective->SetMaximization();
+  // [END objective]
+
+  // [START solve]
+  const MPSolver::ResultStatus result_status = solver.Solve();
+  // Check that the problem has an optimal solution.
+  if (result_status != MPSolver::OPTIMAL) {
+    LOG(FATAL) << "The problem does not have an optimal solution!";
+  }
+  // [END solve]
+
+  // [START print_solution]
+  LOG(INFO) << "Solution:";
+  LOG(INFO) << "Optimal objective value = " << objective->Value();
+  LOG(INFO) << x->name() << " = " << x->solution_value();
+  LOG(INFO) << y->name() << " = " << y->solution_value();
+  // [END print_solution]
+}
+}  // namespace operations_research
+
+int main(int argc, char** argv) {
+  operations_research::LinearProgrammingExample();
+  return EXIT_SUCCESS;
+}
+// [END program]