diff --git a/ortools/sat/doc/scheduling.md b/ortools/sat/doc/scheduling.md
index 481f92f68c..1a5f9d2415 100644
--- a/ortools/sat/doc/scheduling.md
+++ b/ortools/sat/doc/scheduling.md
@@ -253,6 +253,264 @@ public class CodeSamplesSat
 ## NoOverlap constraint
 
 A no overlap constraint simply states that all intervals are disjoint.
+It is build with a list of interval variables. Fixed intervals are useful to
+exclude part of the timeline.
+
+### Python code
+
+```python
+"""Code sample to demonstrates how to build a no overlap constraint."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from ortools.sat.python import cp_model
+
+
+def NoOverlapSample():
+  """No overlap sample with fixed activities."""
+  model = cp_model.CpModel()
+  horizon = 21  # 3 weeks.
+
+  # Task 0, duration 2.
+  start_0 = model.NewIntVar(0, horizon, 'start_0')
+  duration_0 = 2  # Python cp/sat code accept integer variables or constants.
+  end_0 = model.NewIntVar(0, horizon, 'end_0')
+  task_0 = model.NewIntervalVar(start_0, duration_0, end_0, 'task_0')
+  # Task 1, duration 4.
+  start_1 = model.NewIntVar(0, horizon, 'start_1')
+  duration_1 = 4  # Python cp/sat code accept integer variables or constants.
+  end_1 = model.NewIntVar(0, horizon, 'end_1')
+  task_1 = model.NewIntervalVar(start_1, duration_1, end_1, 'task_1')
+
+  # Task 2, duration 3.
+  start_2 = model.NewIntVar(0, horizon, 'start_2')
+  duration_2 = 3  # Python cp/sat code accept integer variables or constants.
+  end_2 = model.NewIntVar(0, horizon, 'end_2')
+  task_2 = model.NewIntervalVar(start_2, duration_2, end_2, 'task_2')
+
+  # Week ends.
+  weekend_0 = model.NewIntervalVar(5, 2, 7, 'weekend_0')
+  weekend_1 = model.NewIntervalVar(12, 2, 14, 'weekend_1')
+  weekend_2 = model.NewIntervalVar(19, 2, 21, 'weekend_2')
+
+  # No Overlap constraint.
+  model.AddNoOverlap([task_0, task_1, task_2, weekend_0, weekend_1, weekend_2])
+
+  # Makespan objective.
+  obj = model.NewIntVar(0, horizon, 'makespan')
+  model.AddMaxEquality(obj, [end_0, end_1, end_2])
+  model.Minimize(obj)
+
+  # Solve model.
+  solver = cp_model.CpSolver()
+  status = solver.Solve(model)
+
+  if status == cp_model.OPTIMAL:
+    # Print out makespan and the starts of all tasks.
+    print('Optimal Schedule Length: %i' % solver.ObjectiveValue())
+    print('Task 0 starts at %i' % solver.Value(start_0))
+    print('Task 1 starts at %i' % solver.Value(start_1))
+    print('Task 2 starts at %i' % solver.Value(start_2))
+
+
+NoOverlapSample()
+```
+
+### C++ code
+
+```cpp
+#include "ortools/sat/cp_model.pb.h"
+#include "ortools/sat/cp_model_solver.h"
+#include "ortools/sat/cp_model_utils.h"
+#include "ortools/sat/model.h"
+
+namespace operations_research {
+namespace sat {
+
+void NoOverlapSample() {
+  CpModelProto cp_model;
+  const int kHorizon = 21;  // 3 weeks.
+
+  auto new_variable = [&cp_model](int64 lb, int64 ub) {
+    CHECK_LE(lb, ub);
+    const int index = cp_model.variables_size();
+    IntegerVariableProto* const var = cp_model.add_variables();
+    var->add_domain(lb);
+    var->add_domain(ub);
+    return index;
+  };
+
+  auto new_constant = [&new_variable](int64 v) { return new_variable(v, v); };
+
+  auto new_interval = [&cp_model](int start, int duration, int end) {
+    const int index = cp_model.constraints_size();
+    IntervalConstraintProto* const interval =
+        cp_model.add_constraints()->mutable_interval();
+    interval->set_start(start);
+    interval->set_size(duration);
+    interval->set_end(end);
+    return index;
+  };
+
+  auto new_fixed_interval = [&cp_model, &new_constant](int64 start,
+                                                       int64 duration) {
+    const int index = cp_model.constraints_size();
+    IntervalConstraintProto* const interval =
+        cp_model.add_constraints()->mutable_interval();
+    interval->set_start(new_constant(start));
+    interval->set_size(new_constant(duration));
+    interval->set_end(new_constant(start + duration));
+    return index;
+  };
+
+  auto add_no_overlap = [&cp_model](const std::vector<int>& intervals) {
+    NoOverlapConstraintProto* const no_overlap =
+        cp_model.add_constraints()->mutable_no_overlap();
+    for (const int i : intervals) {
+      no_overlap->add_intervals(i);
+    }
+  };
+
+  auto add_precedence = [&cp_model](int before, int after) {
+    LinearConstraintProto* const lin =
+        cp_model.add_constraints()->mutable_linear();
+    lin->add_vars(after);
+    lin->add_coeffs(1L);
+    lin->add_vars(before);
+    lin->add_coeffs(-1L);
+    lin->add_domain(0);
+    lin->add_domain(kint64max);
+  };
+
+  // Task 0, duration 2.
+  const int start_0 = new_variable(0, kHorizon);
+  const int duration_0 = new_constant(2);
+  const int end_0 = new_variable(0, kHorizon);
+  const int task_0 = new_interval(start_0, duration_0, end_0);
+
+  // Task 1, duration 4.
+  const int start_1 = new_variable(0, kHorizon);
+  const int duration_1 = new_constant(4);
+  const int end_1 = new_variable(0, kHorizon);
+  const int task_1 = new_interval(start_1, duration_1, end_1);
+
+  // Task 2, duration 3.
+  const int start_2 = new_variable(0, kHorizon);
+  const int duration_2 = new_constant(3);
+  const int end_2 = new_variable(0, kHorizon);
+  const int task_2 = new_interval(start_2, duration_2, end_2);
+
+  // Week ends.
+  const int weekend_0 = new_fixed_interval(5, 2);
+  const int weekend_1 = new_fixed_interval(12, 2);
+  const int weekend_2 = new_fixed_interval(19, 2);
+
+  // No Overlap constraint.
+  add_no_overlap({task_0, task_1, task_2, weekend_0, weekend_1, weekend_2});
+
+  // Makespan.
+  const int makespan = new_variable(0, kHorizon);
+  add_precedence(end_0, makespan);
+  add_precedence(end_1, makespan);
+  add_precedence(end_2, makespan);
+  CpObjectiveProto* const obj = cp_model.mutable_objective();
+  obj->add_vars(makespan);
+  obj->add_coeffs(1);  // Minimization.
+
+  // Solving part.
+  Model model;
+  LOG(INFO) << CpModelStats(cp_model);
+  const CpSolverResponse response = SolveCpModel(cp_model, &model);
+  LOG(INFO) << CpSolverResponseStats(response);
+
+  if (response.status() == CpSolverStatus::OPTIMAL) {
+    LOG(INFO) << "Optimal Schedule Length: " << response.objective_value();
+    LOG(INFO) << "Task 0 starts at " << response.solution(start_0);
+    LOG(INFO) << "Task 1 starts at " << response.solution(start_1);
+    LOG(INFO) << "Task 2 starts at " << response.solution(start_2);
+  }
+}
+
+
+}  // namespace sat
+}  // namespace operations_research
+
+int main() {
+  operations_research::sat::NoOverlapSample();
+
+  return EXIT_SUCCESS;
+}
+```
+
+### C\# code
+
+```cs
+using System;
+using Google.OrTools.Sat;
+
+public class CodeSamplesSat
+{
+  static void NoOverlapSample()
+  {
+    CpModel model = new CpModel();
+    int horizon = 21;
+
+    // Task 0, duration 2.
+    IntVar start_0 = model.NewIntVar(0, horizon, "start_0");
+    int duration_0 = 2;
+    IntVar end_0 = model.NewIntVar(0, horizon, "end_0");
+    IntervalVar task_0 =
+        model.NewIntervalVar(start_0, duration_0, end_0, "task_0");
+
+    //  Task 1, duration 4.
+    IntVar start_1 = model.NewIntVar(0, horizon, "start_1");
+    int duration_1 = 4;
+    IntVar end_1 = model.NewIntVar(0, horizon, "end_1");
+    IntervalVar task_1 =
+        model.NewIntervalVar(start_1, duration_1, end_1, "task_1");
+
+    // Task 2, duration 3.
+    IntVar start_2 = model.NewIntVar(0, horizon, "start_2");
+    int duration_2 = 3;
+    IntVar end_2 = model.NewIntVar(0, horizon, "end_2");
+    IntervalVar task_2 =
+        model.NewIntervalVar(start_2, duration_2, end_2, "task_2");
+
+    // Week ends.
+    IntervalVar weekend_0 = model.NewIntervalVar(5, 2, 7, "weekend_0");
+    IntervalVar weekend_1 = model.NewIntervalVar(12, 2, 14, "weekend_1");
+    IntervalVar weekend_2 = model.NewIntervalVar(19, 2, 21, "weekend_2");
+
+    // No Overlap constraint.
+    model.AddNoOverlap(new IntervalVar[] {task_0, task_1, task_2, weekend_0,
+                                          weekend_1, weekend_2});
+
+    // Makespan objective.
+    IntVar obj = model.NewIntVar(0, horizon, "makespan");
+    model.AddMaxEquality(obj, new IntVar[] {end_0, end_1, end_2});
+    model.Minimize(obj);
+
+    // Creates a solver and solves the model.
+    CpSolver solver = new CpSolver();
+    CpSolverStatus status = solver.Solve(model);
+
+    if (status == CpSolverStatus.Optimal)
+    {
+      Console.WriteLine("Optimal Schedule Length: " + solver.ObjectiveValue);
+      Console.WriteLine("Task 0 starts at " + solver.Value(start_0));
+      Console.WriteLine("Task 1 starts at " + solver.Value(start_1));
+      Console.WriteLine("Task 2 starts at " + solver.Value(start_2));
+    }
+  }
+
+  static void Main()
+  {
+    NoOverlapSample();
+  }
+}
+```
 
 ## Cumulative constraint
 
@@ -262,6 +520,8 @@ at that time point is less than a given capacity.
 
 ## Alternative resources for one interval
 
+## Ranking or tasks in a disjunctive resource
+
 ## Transitions in a disjunctive resource
 
 ## Precedences between intervals
diff --git a/ortools/sat/samples/no_overlap_sample.cc b/ortools/sat/samples/no_overlap_sample.cc
new file mode 100644
index 0000000000..3dc68b2680
--- /dev/null
+++ b/ortools/sat/samples/no_overlap_sample.cc
@@ -0,0 +1,134 @@
+// Copyright 2010-2017 Google
+// 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.
+
+#include "ortools/sat/cp_model.pb.h"
+#include "ortools/sat/cp_model_solver.h"
+#include "ortools/sat/cp_model_utils.h"
+#include "ortools/sat/model.h"
+
+namespace operations_research {
+namespace sat {
+
+void NoOverlapSample() {
+  CpModelProto cp_model;
+  const int kHorizon = 21;  // 3 weeks.
+
+  auto new_variable = [&cp_model](int64 lb, int64 ub) {
+    CHECK_LE(lb, ub);
+    const int index = cp_model.variables_size();
+    IntegerVariableProto* const var = cp_model.add_variables();
+    var->add_domain(lb);
+    var->add_domain(ub);
+    return index;
+  };
+
+  auto new_constant = [&new_variable](int64 v) { return new_variable(v, v); };
+
+  auto new_interval = [&cp_model](int start, int duration, int end) {
+    const int index = cp_model.constraints_size();
+    IntervalConstraintProto* const interval =
+        cp_model.add_constraints()->mutable_interval();
+    interval->set_start(start);
+    interval->set_size(duration);
+    interval->set_end(end);
+    return index;
+  };
+
+  auto new_fixed_interval = [&cp_model, &new_constant](int64 start,
+                                                       int64 duration) {
+    const int index = cp_model.constraints_size();
+    IntervalConstraintProto* const interval =
+        cp_model.add_constraints()->mutable_interval();
+    interval->set_start(new_constant(start));
+    interval->set_size(new_constant(duration));
+    interval->set_end(new_constant(start + duration));
+    return index;
+  };
+
+  auto add_no_overlap = [&cp_model](const std::vector<int>& intervals) {
+    NoOverlapConstraintProto* const no_overlap =
+        cp_model.add_constraints()->mutable_no_overlap();
+    for (const int i : intervals) {
+      no_overlap->add_intervals(i);
+    }
+  };
+
+  auto add_precedence = [&cp_model](int before, int after) {
+    LinearConstraintProto* const lin =
+        cp_model.add_constraints()->mutable_linear();
+    lin->add_vars(after);
+    lin->add_coeffs(1L);
+    lin->add_vars(before);
+    lin->add_coeffs(-1L);
+    lin->add_domain(0);
+    lin->add_domain(kint64max);
+  };
+
+  // Task 0, duration 2.
+  const int start_0 = new_variable(0, kHorizon);
+  const int duration_0 = new_constant(2);
+  const int end_0 = new_variable(0, kHorizon);
+  const int task_0 = new_interval(start_0, duration_0, end_0);
+
+  // Task 1, duration 4.
+  const int start_1 = new_variable(0, kHorizon);
+  const int duration_1 = new_constant(4);
+  const int end_1 = new_variable(0, kHorizon);
+  const int task_1 = new_interval(start_1, duration_1, end_1);
+
+  // Task 2, duration 3.
+  const int start_2 = new_variable(0, kHorizon);
+  const int duration_2 = new_constant(3);
+  const int end_2 = new_variable(0, kHorizon);
+  const int task_2 = new_interval(start_2, duration_2, end_2);
+
+  // Week ends.
+  const int weekend_0 = new_fixed_interval(5, 2);
+  const int weekend_1 = new_fixed_interval(12, 2);
+  const int weekend_2 = new_fixed_interval(19, 2);
+
+  // No Overlap constraint.
+  add_no_overlap({task_0, task_1, task_2, weekend_0, weekend_1, weekend_2});
+
+  // Makespan.
+  const int makespan = new_variable(0, kHorizon);
+  add_precedence(end_0, makespan);
+  add_precedence(end_1, makespan);
+  add_precedence(end_2, makespan);
+  CpObjectiveProto* const obj = cp_model.mutable_objective();
+  obj->add_vars(makespan);
+  obj->add_coeffs(1);  // Minimization.
+
+  // Solving part.
+  Model model;
+  LOG(INFO) << CpModelStats(cp_model);
+  const CpSolverResponse response = SolveCpModel(cp_model, &model);
+  LOG(INFO) << CpSolverResponseStats(response);
+
+  if (response.status() == CpSolverStatus::OPTIMAL) {
+    LOG(INFO) << "Optimal Schedule Length: " << response.objective_value();
+    LOG(INFO) << "Task 0 starts at " << response.solution(start_0);
+    LOG(INFO) << "Task 1 starts at " << response.solution(start_1);
+    LOG(INFO) << "Task 2 starts at " << response.solution(start_2);
+  }
+}
+
+
+}  // namespace sat
+}  // namespace operations_research
+
+int main() {
+  operations_research::sat::NoOverlapSample();
+
+  return EXIT_SUCCESS;
+}
diff --git a/ortools/sat/samples/no_overlap_sample.cs b/ortools/sat/samples/no_overlap_sample.cs
new file mode 100644
index 0000000000..9d51bbc913
--- /dev/null
+++ b/ortools/sat/samples/no_overlap_sample.cs
@@ -0,0 +1,76 @@
+// Copyright 2010-2017 Google
+// 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.
+
+using System;
+using Google.OrTools.Sat;
+
+public class CodeSamplesSat
+{
+  static void NoOverlapSample()
+  {
+    CpModel model = new CpModel();
+    int horizon = 21;
+
+    // Task 0, duration 2.
+    IntVar start_0 = model.NewIntVar(0, horizon, "start_0");
+    int duration_0 = 2;
+    IntVar end_0 = model.NewIntVar(0, horizon, "end_0");
+    IntervalVar task_0 =
+        model.NewIntervalVar(start_0, duration_0, end_0, "task_0");
+
+    //  Task 1, duration 4.
+    IntVar start_1 = model.NewIntVar(0, horizon, "start_1");
+    int duration_1 = 4;
+    IntVar end_1 = model.NewIntVar(0, horizon, "end_1");
+    IntervalVar task_1 =
+        model.NewIntervalVar(start_1, duration_1, end_1, "task_1");
+
+    // Task 2, duration 3.
+    IntVar start_2 = model.NewIntVar(0, horizon, "start_2");
+    int duration_2 = 3;
+    IntVar end_2 = model.NewIntVar(0, horizon, "end_2");
+    IntervalVar task_2 =
+        model.NewIntervalVar(start_2, duration_2, end_2, "task_2");
+
+    // Week ends.
+    IntervalVar weekend_0 = model.NewIntervalVar(5, 2, 7, "weekend_0");
+    IntervalVar weekend_1 = model.NewIntervalVar(12, 2, 14, "weekend_1");
+    IntervalVar weekend_2 = model.NewIntervalVar(19, 2, 21, "weekend_2");
+
+    // No Overlap constraint.
+    model.AddNoOverlap(new IntervalVar[] {task_0, task_1, task_2, weekend_0,
+                                          weekend_1, weekend_2});
+
+    // Makespan objective.
+    IntVar obj = model.NewIntVar(0, horizon, "makespan");
+    model.AddMaxEquality(obj, new IntVar[] {end_0, end_1, end_2});
+    model.Minimize(obj);
+
+    // Creates a solver and solves the model.
+    CpSolver solver = new CpSolver();
+    CpSolverStatus status = solver.Solve(model);
+
+    if (status == CpSolverStatus.Optimal)
+    {
+      Console.WriteLine("Optimal Schedule Length: " + solver.ObjectiveValue);
+      Console.WriteLine("Task 0 starts at " + solver.Value(start_0));
+      Console.WriteLine("Task 1 starts at " + solver.Value(start_1));
+      Console.WriteLine("Task 2 starts at " + solver.Value(start_2));
+    }
+  }
+
+  static void Main()
+  {
+    NoOverlapSample();
+  }
+}
diff --git a/ortools/sat/samples/no_overlap_sample.py b/ortools/sat/samples/no_overlap_sample.py
new file mode 100644
index 0000000000..fd395094cd
--- /dev/null
+++ b/ortools/sat/samples/no_overlap_sample.py
@@ -0,0 +1,69 @@
+# Copyright 2010-2017 Google
+# 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.
+"""Code sample to demonstrates how to build a no overlap constraint."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from ortools.sat.python import cp_model
+
+
+def NoOverlapSample():
+  """No overlap sample with fixed activities."""
+  model = cp_model.CpModel()
+  horizon = 21  # 3 weeks.
+
+  # Task 0, duration 2.
+  start_0 = model.NewIntVar(0, horizon, 'start_0')
+  duration_0 = 2  # Python cp/sat code accept integer variables or constants.
+  end_0 = model.NewIntVar(0, horizon, 'end_0')
+  task_0 = model.NewIntervalVar(start_0, duration_0, end_0, 'task_0')
+  # Task 1, duration 4.
+  start_1 = model.NewIntVar(0, horizon, 'start_1')
+  duration_1 = 4  # Python cp/sat code accept integer variables or constants.
+  end_1 = model.NewIntVar(0, horizon, 'end_1')
+  task_1 = model.NewIntervalVar(start_1, duration_1, end_1, 'task_1')
+
+  # Task 2, duration 3.
+  start_2 = model.NewIntVar(0, horizon, 'start_2')
+  duration_2 = 3  # Python cp/sat code accept integer variables or constants.
+  end_2 = model.NewIntVar(0, horizon, 'end_2')
+  task_2 = model.NewIntervalVar(start_2, duration_2, end_2, 'task_2')
+
+  # Week ends.
+  weekend_0 = model.NewIntervalVar(5, 2, 7, 'weekend_0')
+  weekend_1 = model.NewIntervalVar(12, 2, 14, 'weekend_1')
+  weekend_2 = model.NewIntervalVar(19, 2, 21, 'weekend_2')
+
+  # No Overlap constraint.
+  model.AddNoOverlap([task_0, task_1, task_2, weekend_0, weekend_1, weekend_2])
+
+  # Makespan objective.
+  obj = model.NewIntVar(0, horizon, 'makespan')
+  model.AddMaxEquality(obj, [end_0, end_1, end_2])
+  model.Minimize(obj)
+
+  # Solve model.
+  solver = cp_model.CpSolver()
+  status = solver.Solve(model)
+
+  if status == cp_model.OPTIMAL:
+    # Print out makespan and the starts of all tasks.
+    print('Optimal Schedule Length: %i' % solver.ObjectiveValue())
+    print('Task 0 starts at %i' % solver.Value(start_0))
+    print('Task 1 starts at %i' % solver.Value(start_1))
+    print('Task 2 starts at %i' % solver.Value(start_2))
+
+
+NoOverlapSample()