examples/notebook/contrib/car.ipynb
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First, you must install ortools package in this colab.
%pip install ortools
Car sequencing in Google CP Solver.
This model is based on the car sequencing model in Pascal Van Hentenryck 'The OPL Optimization Programming Language', page 184ff.
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/
import sys
from ortools.constraint_solver import pywrapcp
def main(num_sol=3):
# Create the solver.
solver = pywrapcp.Solver("Car sequence")
#
# data
#
nbCars = 6
nbOptions = 5
nbSlots = 10
Cars = list(range(nbCars))
Options = list(range(nbOptions))
Slots = list(range(nbSlots))
# car 0 1 2 3 4 5
demand = [1, 1, 2, 2, 2, 2]
option = [
# car 0 1 2 3 4 5
[1, 0, 0, 0, 1, 1], # option 1
[0, 0, 1, 1, 0, 1], # option 2
[1, 0, 0, 0, 1, 0], # option 3
[1, 1, 0, 1, 0, 0], # option 4
[0, 0, 1, 0, 0, 0] # option 5
]
capacity = [(1, 2), (2, 3), (1, 3), (2, 5), (1, 5)]
optionDemand = [
sum([demand[j] * option[i][j] for j in Cars]) for i in Options
]
#
# declare variables
#
slot = [solver.IntVar(0, nbCars - 1, "slot[%i]" % i) for i in Slots]
setup = {}
for i in Options:
for j in Slots:
setup[(i, j)] = solver.IntVar(0, 1, "setup[%i,%i]" % (i, j))
setup_flat = [setup[i, j] for i in Options for j in Slots]
#
# constraints
#
for c in Cars:
b = [solver.IsEqualCstVar(slot[s], c) for s in Slots]
solver.Add(solver.Sum(b) == demand[c])
for o in Options:
for s in range(0, nbSlots - capacity[o][1] + 1):
b = [setup[o, j] for j in range(s, s + capacity[o][1] - 1)]
solver.Add(solver.Sum(b) <= capacity[o][0])
for o in Options:
for s in Slots:
solver.Add(setup[(o, s)] == solver.Element(option[o], slot[s]))
for o in Options:
for i in range(optionDemand[o]):
s_range = list(range(0, nbSlots - (i + 1) * capacity[o][1]))
ss = [setup[o, s] for s in s_range]
cc = optionDemand[o] - (i + 1) * capacity[o][0]
if len(ss) > 0 and cc >= 0:
solver.Add(solver.Sum(ss) >= cc)
#
# search and result
#
db = solver.Phase(slot + setup_flat, solver.CHOOSE_FIRST_UNBOUND,
solver.ASSIGN_MIN_VALUE)
solver.NewSearch(db)
num_solutions = 0
while solver.NextSolution():
print("slot:%s" % ",".join([str(slot[i].Value()) for i in Slots]))
print("setup:")
for o in Options:
print("%i/%i:" % (capacity[o][0], capacity[o][1]), end=" ")
for s in Slots:
print(setup[o, s].Value(), end=" ")
print()
print()
num_solutions += 1
if num_solutions >= num_sol:
break
solver.EndSearch()
print()
print("num_solutions:", num_solutions)
print("failures:", solver.Failures())
print("branches:", solver.Branches())
print("WallTime:", solver.WallTime())
num_sol = 3
if len(sys.argv) > 1:
num_sol = int(sys.argv[1])
main(num_sol)