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ortools-clone/examples/python/crew.py
Chris Drake 8927b03942 Get rid of unnecessary string imports
Some of these imports are not used.
The rest of them only import string to use the string.atoi function.
But string.atoi(s) on a string input is identical to just int(s).
See the docs: "deprecated since 2.0".
2015-12-16 00:05:33 -08:00

225 lines
6.3 KiB
Python

# 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.
"""
Crew allocation problem in Google CP Solver.
From Gecode example crew
examples/crew.cc
'''
* Example: Airline crew allocation
*
* Assign 20 flight attendants to 10 flights. Each flight needs a certain
* number of cabin crew, and they have to speak certain languages.
* Every cabin crew member has two flights off after an attended flight.
*
'''
Compare with the following models:
* MiniZinc: http://www.hakank.org/minizinc/crew.mzn
* Comet : http://www.hakank.org/comet/crew.co
* ECLiPSe : http://hakank.org/eclipse/crew.ecl
* SICStus : http://hakank.org/sicstus/crew.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
from ortools.constraint_solver import pywrapcp
def main(sols=1):
# Create the solver.
solver = pywrapcp.Solver("Crew")
#
# data
#
names = ["Tom",
"David",
"Jeremy",
"Ron",
"Joe",
"Bill",
"Fred",
"Bob",
"Mario",
"Ed",
"Carol",
"Janet",
"Tracy",
"Marilyn",
"Carolyn",
"Cathy",
"Inez",
"Jean",
"Heather",
"Juliet"]
num_persons = len(names) # number of persons
attributes = [
# steward, hostess, french, spanish, german
[1, 0, 0, 0, 1], # Tom = 1
[1, 0, 0, 0, 0], # David = 2
[1, 0, 0, 0, 1], # Jeremy = 3
[1, 0, 0, 0, 0], # Ron = 4
[1, 0, 0, 1, 0], # Joe = 5
[1, 0, 1, 1, 0], # Bill = 6
[1, 0, 0, 1, 0], # Fred = 7
[1, 0, 0, 0, 0], # Bob = 8
[1, 0, 0, 1, 1], # Mario = 9
[1, 0, 0, 0, 0], # Ed = 10
[0, 1, 0, 0, 0], # Carol = 11
[0, 1, 0, 0, 0], # Janet = 12
[0, 1, 0, 0, 0], # Tracy = 13
[0, 1, 0, 1, 1], # Marilyn = 14
[0, 1, 0, 0, 0], # Carolyn = 15
[0, 1, 0, 0, 0], # Cathy = 16
[0, 1, 1, 1, 1], # Inez = 17
[0, 1, 1, 0, 0], # Jean = 18
[0, 1, 0, 1, 1], # Heather = 19
[0, 1, 1, 0, 0] # Juliet = 20
]
# The columns are in the following order:
# staff : Overall number of cabin crew needed
# stewards : How many stewards are required
# hostesses : How many hostesses are required
# french : How many French speaking employees are required
# spanish : How many Spanish speaking employees are required
# german : How many German speaking employees are required
required_crew = [
[4, 1, 1, 1, 1, 1], # Flight 1
[5, 1, 1, 1, 1, 1], # Flight 2
[5, 1, 1, 1, 1, 1], # ..
[6, 2, 2, 1, 1, 1],
[7, 3, 3, 1, 1, 1],
[4, 1, 1, 1, 1, 1],
[5, 1, 1, 1, 1, 1],
[6, 1, 1, 1, 1, 1],
[6, 2, 2, 1, 1, 1], # ...
[7, 3, 3, 1, 1, 1] # Flight 10
]
num_flights = len(required_crew) # number of flights
#
# declare variables
#
crew = {}
for i in range(num_flights):
for j in range(num_persons):
crew[(i, j)] = solver.IntVar(0, 1, "crew[%i,%i]" % (i, j))
crew_flat = [crew[(i, j)] for i in range(num_flights)
for j in range(num_persons)]
# number of working persons
num_working = solver.IntVar(1, num_persons, "num_working")
#
# constraints
#
# number of working persons
solver.Add(num_working == solver.Sum(
[solver.IsGreaterOrEqualCstVar(solver.Sum([crew[(f, p)]
for f in range(num_flights)]), 1)
for p in range(num_persons)]))
for f in range(num_flights):
# size of crew
tmp = [crew[(f, i)] for i in range(num_persons)]
solver.Add(solver.Sum(tmp) == required_crew[f][0])
# attributes and requirements
for j in range(5):
tmp = [attributes[i][j] * crew[(f, i)] for i in range(num_persons)]
solver.Add(solver.Sum(tmp) >= required_crew[f][j + 1])
# after a flight, break for at least two flights
for f in range(num_flights - 2):
for i in range(num_persons):
solver.Add(crew[f, i] + crew[f + 1, i] + crew[f + 2, i] <= 1)
# extra contraint: all must work at least two of the flights
# for i in range(num_persons):
# [solver.Add(solver.Sum([crew[f,i] for f in range(num_flights)]) >= 2) ]
#
# solution and search
#
solution = solver.Assignment()
solution.Add(crew_flat)
solution.Add(num_working)
db = solver.Phase(crew_flat,
solver.CHOOSE_FIRST_UNBOUND,
solver.ASSIGN_MIN_VALUE)
#
# result
#
solver.NewSearch(db)
num_solutions = 0
while solver.NextSolution():
num_solutions += 1
print "Solution #%i" % num_solutions
print "Number working:", num_working.Value()
for i in range(num_flights):
for j in range(num_persons):
print crew[i, j].Value(),
print
print
print "Flights:"
for flight in range(num_flights):
print "Flight", flight, "persons:",
for person in range(num_persons):
if crew[flight, person].Value() == 1:
print names[person],
print
print
print "Crew:"
for person in range(num_persons):
print "%-10s flights" % names[person],
for flight in range(num_flights):
if crew[flight, person].Value() == 1:
print flight,
print
print
if num_solutions >= sols:
break
solver.EndSearch()
print
print "num_solutions:", num_solutions
print "failures:", solver.Failures()
print "branches:", solver.Branches()
print "WallTime:", solver.WallTime()
num_solutions_to_show = 1
if __name__ == "__main__":
if (len(sys.argv) > 1):
num_solutions_to_show = int(sys.argv[1])
main(num_solutions_to_show)