# Copyright 2010 Hakan Kjellerstrand hakank@bonetmail.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@bonetmail.com)
Also see my other Google CP Solver models:
http://www.hakank.org/google_or_tools/
"""
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")