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bus_schedule

examples/notebook/contrib/bus_schedule.ipynb

2016-063.7 KB
Original Source
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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_schedule

<table align="left"> <td> <a href="https://colab.research.google.com/github/google/or-tools/blob/main/examples/notebook/contrib/bus_schedule.ipynb">Run in Google Colab</a> </td> <td> <a href="https://github.com/google/or-tools/blob/main/examples/contrib/bus_schedule.py">View source on GitHub</a> </td> </table>

First, you must install ortools package in this colab.

python
%pip install ortools

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:

This model was created by Hakan Kjellerstrand ([email protected]) Also see my other Google CP Solver models: http://www.hakank.org/google_or_tools/

python
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


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