Clustering of sites using OR tools (CP solver) - python-3.x

Question

I am trying to make clusters of sites based on their distance from each other. I am using or tools cp solver to achieve this. The program runs fine for 40 to 50 number of sites but when i try to run for about 200 sites with each cluster containing 10 sites the program gets stuck and does not give any output. I am using the cp_model for this.
Please below the code I am using :
from ortools.sat.python import cp_model
import pandas as pd,sys,os,requests,re
matrix_data = pd.read_csv(''.join([filepath,'//matrix.csv']),
matrix = matrix_data.values.tolist()
#data = {}
#data['distance_matrix'] = []
distance_matrix = []
for i in matrix:
distance_matrix.append(i)
def main():
"""Entry point of the program."""
num_nodes = len(distance_matrix)
print('Num nodes =', num_nodes)
# Number of groups to split the nodes, must divide num_nodes.
num_groups = 10
# Model.
model = cp_model.CpModel()
# Variables.
neighbors = {}
obj_vars = []
obj_coeffs = []
for n1 in range(num_nodes - 1):
for n2 in range(n1 + 1, num_nodes):
same = model.NewBoolVar('neighbors_%i_%i' % (n1, n2))
neighbors[n1, n2] = same
obj_vars.append(same)
obj_coeffs.append(distance_matrix[n1][n2] + distance_matrix[n2][n1])
# Number of neighborss:
for n in range(num_nodes):
model.Add(sum(neighbors[m, n] for m in range(n)) +
sum(neighbors[n, m] for m in range(n + 1, num_nodes)) ==
group_size - 1)
# Enforce transivity on all triplets.
for n1 in range(num_nodes - 2):
for n2 in range(n1 + 1, num_nodes - 1):
for n3 in range(n2 + 1, num_nodes):
model.Add(
neighbors[n1, n3] + neighbors[n2, n3] + neighbors[n1, n2] != 2)
# Redundant constraints on total sum of neighborss.
model.Add(sum(obj_vars) == num_groups * group_size * (group_size - 1) // 2)
# Minimize weighted sum of arcs.
model.Minimize(
sum(obj_vars[i] * obj_coeffs[i] for i in range(len(obj_vars))))
# Solve and print out the solution.
solver = cp_model.CpSolver()
solver.parameters.log_search_progress = True
solver.parameters.num_search_workers = 6
status = solver.Solve(model)
print(solver.ResponseStats())
visited = set()
for g in range(num_groups):
flonglist = []
flatlist = []
for n in range(num_nodes):
if not n in visited:
visited.add(n)
output = str(n)
for o in range(n + 1, num_nodes):
if solver.BooleanValue(neighbors[n, o]):
visited.add(o)
output += ' ' + str(o)
print('Group', g, ':', output)
print(site_list)
break
if __name__ == '__main__':
main()
print("-- %s seconds ---" % (time.time() - start_time))
The matrix file contain the distance of sites from each other in matrix format.
need some help.