diff --git a/examples/python/wedding_optimal_chart.py b/examples/python/wedding_optimal_chart.py
new file mode 100644
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+++ b/examples/python/wedding_optimal_chart.py
@@ -0,0 +1,179 @@
+#
+# Copyright 2018 Turadg Aleahmad
+#
+# 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.
+
+from __future__ import print_function
+from ortools.constraint_solver import pywrapcp
+from ortools.constraint_solver import solver_parameters_pb2
+
+
+"""
+Finding an optimal wedding seating chart.
+
+From
+Meghan L. Bellows and J. D. Luc Peterson
+"Finding an optimal seating chart for a wedding"
+http://www.improbable.com/news/2012/Optimal-seating-chart.pdf
+http://www.improbable.com/2012/02/12/finding-an-optimal-seating-chart-for-a-wedding
+
+Every year, millions of brides (not to mention their mothers, future
+mothers-in-law, and occasionally grooms) struggle with one of the
+most daunting tasks during the wedding-planning process: the
+seating chart. The guest responses are in, banquet hall is booked,
+menu choices have been made. You think the hard parts are over,
+but you have yet to embark upon the biggest headache of them all.
+In order to make this process easier, we present a mathematical
+formulation that models the seating chart problem. This model can
+be solved to find the optimal arrangement of guests at tables.
+At the very least, it can provide a starting point and hopefully
+minimize stress and arguments…
+
+Adapted from https://github.com/google/or-tools/blob/master/examples/csharp/wedding_optimal_chart.cs
+"""
+def main():
+	# Instantiate a CP solver.
+	parameters = pywrapcp.Solver.DefaultSolverParameters()
+	solver = pywrapcp.Solver("WeddingOptimalChart", parameters)
+
+	#
+	# Data
+	#
+
+	# Easy problem (from the paper)
+	n = 2  # number of tables
+	a = 10 # maximum number of guests a table can seat
+	b = 1  # minimum number of people each guest knows at their table
+
+	# Slightly harder problem (also from the paper)
+	# n = 5 # number of tables
+	# a = 4 # maximum number of guests a table can seat
+	# b = 1 # minimum number of people each guest knows at their table
+
+	# Connection matrix: who knows who, and how strong
+	# is the relation
+	C = [
+		[ 1,50, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0],
+		[50, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0],
+		[ 1, 1, 1,50, 1, 1, 1, 1,10, 0, 0, 0, 0, 0, 0, 0, 0],
+		[ 1, 1,50, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0],
+		[ 1, 1, 1, 1, 1,50, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0],
+		[ 1, 1, 1, 1,50, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0],
+		[ 1, 1, 1, 1, 1, 1, 1,50, 1, 0, 0, 0, 0, 0, 0, 0, 0],
+		[ 1, 1, 1, 1, 1, 1,50, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0],
+		[ 1, 1,10, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,50, 1, 1, 1, 1, 1, 1],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0,50, 1, 1, 1, 1, 1, 1, 1],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1]
+	]
+
+		# Names of the guests. B: Bride side, G: Groom side
+	names =  [
+		"Deb (B)",
+		"John (B)",
+		"Martha (B)",
+		"Travis (B)",
+		"Allan (B)",
+		"Lois (B)",
+		"Jayne (B)",
+		"Brad (B)",
+		"Abby (B)",
+		"Mary Helen (G)",
+		"Lee (G)",
+		"Annika (G)",
+		"Carl (G)",
+		"Colin (G)",
+		"Shirley (G)",
+		"DeAnn (G)",
+		"Lori (G)"
+	]
+
+	m = len(C)
+
+	NRANGE = range(n)
+	MRANGE = range(m)
+
+	#
+	# Decision variables
+	#
+	tables = [solver.IntVar(0, n-1, 'x[%i]' % i) for i in MRANGE]
+
+	z = solver.Sum([ C[j][k] * (tables[j] == tables[k])
+									for j in MRANGE
+									for k in MRANGE if j < k])
+
+	#
+	# Constraints
+	#
+	for i in NRANGE:
+		minGuests = [
+			(tables[j] == i) * (tables[k] == i)
+			for j in MRANGE
+			for k in MRANGE if j < k and C[j][k] > 0
+		]
+		solver.Add(solver.Sum(minGuests) >= b);
+
+		maxGuests = [tables[j] == i for j in MRANGE]
+		solver.Add(solver.Sum(maxGuests) <= a);
+
+	# Symmetry breaking
+	solver.Add(tables[0] == 0)
+
+	#
+	# Objective
+	#
+	objective = solver.Maximize(z, 1)
+
+	#
+	# Search
+	#
+	db = solver.Phase(tables,
+		solver.INT_VAR_DEFAULT,
+		solver.INT_VALUE_DEFAULT);
+
+	solver.NewSearch(db, [objective])
+
+	while solver.NextSolution():
+		print("z:", z)
+		print("Table: ")
+		for j in MRANGE:
+			print(tables[j].Value(), " ");
+		print()
+
+		for i in NRANGE:
+			print("Table %d: " % i);
+			for j in MRANGE:
+				if tables[j].Value() == i:
+					print(names[j] + " ")
+			print()
+
+		print()
+
+	solver.EndSearch()
+
+	print()
+	print("Solutions: %d" % solver.Solutions())
+	print("WallTime: %dms" % solver.WallTime())
+	print("Failures: %d" % solver.Failures())
+	print("Branches: %d" % solver.Branches())
+
+
+
+
+if __name__ == '__main__':
+	main()