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bus_schedule.py
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bus_schedule.py
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# Copyright 2010 Hakan Kjellerstrand [email protected]
#
# 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 ([email protected])
Also see my other Google CP Solver models:
http://www.hakank.org/google_or_tools/
"""
import sys
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))], end=" ")
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)