diff --git a/ortools/linear_solver/samples/AssignmentMb.cs b/ortools/linear_solver/samples/AssignmentMb.cs
new file mode 100644
index 0000000000..a1213c7ff0
--- /dev/null
+++ b/ortools/linear_solver/samples/AssignmentMb.cs
@@ -0,0 +1,129 @@
+// Copyright 2010-2022 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]
+using System;
+using Google.OrTools.ModelBuilder;
+// [END import]
+
+public class AssignmentMb
+{
+    static void Main()
+    {
+        // Data.
+        // [START data_model]
+        int[,] costs = {
+            { 90, 80, 75, 70 }, { 35, 85, 55, 65 }, { 125, 95, 90, 95 }, { 45, 110, 95, 115 }, { 50, 100, 90, 100 },
+        };
+        int numWorkers = costs.GetLength(0);
+        int numTasks = costs.GetLength(1);
+        // [END data_model]
+
+       // [START model]
+        ModelBuilder model = new ModelBuilder();
+        // [END model]
+
+        // Variables.
+        // [START variables]
+        // x[i, j] is an array of 0-1 variables, which will be 1
+        // if worker i is assigned to task j.
+        Variable[,] x = new Variable[numWorkers, numTasks];
+        for (int i = 0; i < numWorkers; ++i)
+        {
+            for (int j = 0; j < numTasks; ++j)
+            {
+                x[i, j] = model.NewBoolVar($"worker_{i}_task_{j}");
+            }
+        }
+        // [END variables]
+
+        // Constraints
+        // [START constraints]
+        // Each worker is assigned to at most one task.
+        for (int i = 0; i < numWorkers; ++i)
+        {
+            var assignedWork = LinearExpr.NewBuilder();
+            for (int j = 0; j < numTasks; ++j)
+            {
+                assignedWork.Add(x[i, j]);
+            }
+            model.Add(assignedWork <= 1); 
+        }
+
+        // Each task is assigned to exactly one worker.
+        for (int j = 0; j < numTasks; ++j)
+        {
+            var assignedWorker = LinearExpr.NewBuilder();
+            for (int i = 0; i < numWorkers; ++i)
+            {
+                assignedWorker.Add(x[i, j]);
+            }
+            model.Add(assignedWorker == 1); 
+        }
+        // [END constraints]
+
+        // Objective
+        // [START objective]
+        var objective = LinearExpr.NewBuilder();
+        for (int i = 0; i < numWorkers; ++i)
+        {
+            for (int j = 0; j < numTasks; ++j)
+            {
+                objective.AddTerm(x[i, j], costs[i, j]);
+            }
+        }
+        model.Minimize(objective);
+        // [END objective]
+
+        // [START solver]
+        // Create the model solver with the SCIP backend.
+        ModelSolver solver = new ModelSolver("SCIP");
+        if (!solver.SolverIsSupported())
+        {
+            return;
+        }
+        // [END solver]
+        
+        // Solve
+        // [START solve]
+        SolveStatus resultStatus = solver.Solve(model);
+        // [END solve]
+
+        // Print solution.
+        // [START print_solution]
+        // Check that the problem has a feasible solution.
+        if (resultStatus == SolverStatus.OPTIMAL || resultStatus == SolverStatus.FEASIBLE)
+        {
+            Console.WriteLine($"Total cost: {solver.ObjectiveValue}\n");
+            for (int i = 0; i < numWorkers; ++i)
+            {
+                for (int j = 0; j < numTasks; ++j)
+                {
+                    // Test if x[i, j] is 0 or 1 (with tolerance for floating point
+                    // arithmetic).
+                    if (solver.Value(x[i, j]) > 0.9)
+                    {
+                        Console.WriteLine($"Worker {i} assigned to task {j}. Cost: {costs[i, j]}");
+                    }
+                }
+            }
+        }
+        else
+        {
+            Console.WriteLine("No solution found.");
+        }
+        // [END print_solution]
+    }
+}
+// [END program]
diff --git a/ortools/linear_solver/samples/BinPackingMb.cs b/ortools/linear_solver/samples/BinPackingMb.cs
new file mode 100644
index 0000000000..31fa1a6d4b
--- /dev/null
+++ b/ortools/linear_solver/samples/BinPackingMb.cs
@@ -0,0 +1,131 @@
+// Copyright 2010-2022 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]
+using System;
+using Google.OrTools.ModelBuilder;
+// [END import]
+
+// [START program_part1]
+public class BinPackingMb
+{
+    // [START data_model]
+    class DataModel
+    {
+        public static double[] Weights = { 48, 30, 19, 36, 36, 27, 42, 42, 36, 24, 30 };
+        public int NumItems = Weights.Length;
+        public int NumBins = Weights.Length;
+        public double BinCapacity = 100.0;
+    }
+    // [END data_model]
+    public static void Main()
+    {
+        // [START data]
+        DataModel data = new DataModel();
+        // [END data]
+        // [END program_part1]
+
+        // [START model]
+        ModelBuilder model = new ModelBuilder();
+        // [END model]
+
+        // [START program_part2]
+        // [START variables]
+        Variable[,] x = new Variable[data.NumItems, data.NumBins];
+        for (int i = 0; i < data.NumItems; i++)
+        {
+            for (int j = 0; j < data.NumBins; j++)
+            {
+                x[i, j] = model.NewBoolVar($"x_{i}_{j}");
+            }
+        }
+        Variable[] y = new Variable[data.NumBins];
+        for (int j = 0; j < data.NumBins; j++)
+        {
+            y[j] = model.NewBoolVar($"y_{j}");
+        }
+        // [END variables]
+
+        // [START constraints]
+        for (int i = 0; i < data.NumItems; ++i)
+        {
+            var assignedWork = LinearExpr.NewBuilder();
+            for (int j = 0; j < data.NumBins; ++j)
+            {
+                assignedWork.Add(x[i, j]);
+            }
+            model.Add(assignedWork == 1);
+        }
+
+        for (int j = 0; j < data.NumBins; ++j)
+        {
+            var load = LinearExpr.NewBuilder();
+            for (int i = 0; i < data.NumItems; ++i)
+            {
+                load.AddTerm(x[i, j], DataModel.Weights[i]);
+            }
+            model.Add(y[j] * data.BinCapacity >= load);
+        }
+        // [END constraints]
+
+        // [START objective]
+        model.Minimize(LinearExpr.Sum(y));
+        // [END objective]
+
+        // [START solver]
+        // Create the model solver with the SCIP backend.
+        ModelSolver solver = new ModelSolver("SCIP");
+        if (!solver.SolverIsSupported())
+        {
+            return;
+        }
+        // [END solver]
+        
+        // [START solve]
+        SolveStatus resultStatus = solver.Solve(model);
+        // [END solve]
+
+        // [START print_solution]
+        // Check that the problem has an optimal solution.
+        if (resultStatus != SolveStatus.OPTIMAL)
+        {
+            Console.WriteLine("The problem does not have an optimal solution!");
+            return;
+        }
+        Console.WriteLine($"Number of bins used: {solver.ObjectiveValue}");
+        double TotalWeight = 0.0;
+        for (int j = 0; j < data.NumBins; ++j)
+        {
+            double BinWeight = 0.0;
+            if (solver.Value(y[j]) == 1)
+            {
+                Console.WriteLine($"Bin {j}");
+                for (int i = 0; i < data.NumItems; ++i)
+                {
+                    if (solver.Value(x[i, j]) == 1)
+                    {
+                        Console.WriteLine($"Item {i} weight: {DataModel.Weights[i]}");
+                        BinWeight += DataModel.Weights[i];
+                    }
+                }
+                Console.WriteLine($"Packed bin weight: {BinWeight}");
+                TotalWeight += BinWeight;
+            }
+        }
+        Console.WriteLine($"Total packed weight: {TotalWeight}");
+        // [END print_solution]
+    }
+}
+// [END program_part2]
+// [END program]
diff --git a/ortools/linear_solver/samples/SimpleMipProgramMb.cs b/ortools/linear_solver/samples/SimpleMipProgramMb.cs
index fe0a81ac43..b0f87cb6b5 100644
--- a/ortools/linear_solver/samples/SimpleMipProgramMb.cs
+++ b/ortools/linear_solver/samples/SimpleMipProgramMb.cs
@@ -51,7 +51,7 @@ public class SimpleMipProgramMb
         // [END objective]
 
         // [START solver]
-        // Create the model solver with the GLOP backend.
+        // Create the model solver with the SCIP backend.
         ModelSolver solver = new ModelSolver("SCIP");
         if (!solver.SolverIsSupported())
         {