# 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.

"""

  Bus scheduling in Google CP Solver.


  Problem from Taha "Introduction to Operations Research", page 58.

  This is a slightly more general model than Taha's.

  Compare with the following models:
  * MiniZinc: http://www.hakank.org/minizinc/bus_scheduling.mzn
  * Comet   : http://www.hakank.org/comet/bus_schedule.co
  * ECLiPSe : http://www.hakank.org/eclipse/bus_schedule.ecl
  * Gecode  : http://www.hakank.org/gecode/bus_schedule.cpp
  * Tailor/Essence'  : http://www.hakank.org/tailor/bus_schedule.eprime
  * SICStus: http://hakank.org/sicstus/bus_schedule.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/

"""

import sys
import string
from ortools.constraint_solver import pywrapcp



def main(num_buses_check=0):

    # Create the solver.
    solver = pywrapcp.Solver('Bus scheduling')

    # data
    time_slots = 6
    demands = [8, 10, 7, 12, 4, 4]
    max_num = sum(demands)

    # declare variables
    x = [solver.IntVar(0, max_num, "x%i"%i) for i in range(time_slots)]
    num_buses = solver.IntVar(0, max_num, 'num_buses')

    #
    # constraints
    #
    solver.Add(num_buses == solver.Sum(x))

    # Meet the demands for this and the next time slot
    for i in range(time_slots-1):
        solver.Add(x[i]+x[i+1] >= demands[i])

    # The demand "around the clock"
    solver.Add(x[time_slots-1] + x[0] == demands[time_slots-1])

    if num_buses_check > 0:
        solver.Add(num_buses == num_buses_check)

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

    collector = solver.AllSolutionCollector(solution)
    cargs = [collector]

    # objective
    if num_buses_check == 0:
        objective = solver.Minimize(num_buses, 1)
        cargs.extend([objective])




    solver.Solve(solver.Phase(x,
                              solver.CHOOSE_FIRST_UNBOUND,
                              solver.ASSIGN_MIN_VALUE),
                              cargs)

    num_solutions = collector.SolutionCount()
    num_buses_check_value = 0
    for s in range(num_solutions):
        print "x:", [collector.Value(s, x[i]) for i in range(len(x))],
        num_buses_check_value = collector.Value(s, num_buses)
        print " num_buses:", num_buses_check_value

    print
    print "num_solutions:", num_solutions
    print "failures:", solver.Failures()
    print "branches:", solver.Branches()
    print "WallTime:", solver.WallTime()
    print
    if num_buses_check == 0:
        return num_buses_check_value

if __name__ == '__main__':
    print "Check for minimun number of buses"
    num_buses_check = main()
    print "... got ", num_buses_check, "buses"
    print "All solutions:"
    main(num_buses_check)