# Copyright 2010 Hakan Kjellerstrand hakank@gmail.com
#
# 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.
"""

  Set covering in Google CP Solver.

  Placing of firestations, from Winston 'Operations Research', page 486.

  Compare with the following models:
  * MiniZinc: http://www.hakank.org/minizinc/set_covering.mzn
  * ECLiPSe : http://www.hakank.org/eclipse/set_covering.ecl
  * Comet   : http://www.hakank.org/comet/set_covering.co
  * Gecode  : http://www.hakank.org/gecode/set_covering.cpp
  * SICStus : http://www.hakank.org/sicstus/set_covering.pl


  This model was created by Hakan Kjellerstrand (hakank@gmail.com)
  Also see my other Google CP Solver models:
  http://www.hakank.org/google_or_tools/

"""
from __future__ import print_function
from ortools.constraint_solver import pywrapcp


def main(unused_argv):

  # Create the solver.
  solver = pywrapcp.Solver("Set covering")

  #
  # data
  #
  min_distance = 15
  num_cities = 6

  distance = [[0, 10, 20, 30, 30, 20], [10, 0, 25, 35, 20, 10],
              [20, 25, 0, 15, 30, 20], [30, 35, 15, 0, 15, 25],
              [30, 20, 30, 15, 0, 14], [20, 10, 20, 25, 14, 0]]

  #
  # declare variables
  #
  x = [solver.IntVar(0, 1, "x[%i]" % i) for i in range(num_cities)]

  #
  # constraints
  #

  # objective to minimize
  z = solver.Sum(x)

  # ensure that all cities are covered
  for i in range(num_cities):
    b = [x[j] for j in range(num_cities) if distance[i][j] <= min_distance]
    solver.Add(solver.SumGreaterOrEqual(b, 1))

  objective = solver.Minimize(z, 1)

  #
  # solution and search
  #
  solution = solver.Assignment()
  solution.Add(x)
  solution.AddObjective(z)

  collector = solver.LastSolutionCollector(solution)
  solver.Solve(
      solver.Phase(x + [z], solver.INT_VAR_DEFAULT, solver.INT_VALUE_DEFAULT),
      [collector, objective])

  print("z:", collector.ObjectiveValue(0))
  print("x:", [collector.Value(0, x[i]) for i in range(num_cities)])

  print("failures:", solver.Failures())
  print("branches:", solver.Branches())
  print("WallTime:", solver.WallTime())


if __name__ == "__main__":
  main("cp sample")