149 lines
3.9 KiB
Python
149 lines
3.9 KiB
Python
# Copyright 2010 Hakan Kjellerstrand hakank@bonetmail.com
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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Car sequencing in Google CP Solver.
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This model is based on the car sequencing model in
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Pascal Van Hentenryck
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'The OPL Optimization Programming Language', page 184ff.
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Compare with the following models:
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* MiniZinc: http://hakank.org/minizinc/car.mzn
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* Comet: http://hakank.org/comet/car.co
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This model was created by Hakan Kjellerstrand (hakank@bonetmail.com)
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Also see my other Google CP Solver models: http://www.hakank.org/google_or_tools/
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"""
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import sys
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import string
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from ortools.constraint_solver import pywrapcp
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def main(num_sol=3):
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# Create the solver.
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solver = pywrapcp.Solver('Car sequence')
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#
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# data
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#
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nbCars = 6
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nbOptions = 5
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nbSlots = 10
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Cars = range(nbCars)
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Options = range(nbOptions)
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Slots = range(nbSlots)
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# car 0 1 2 3 4 5
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demand = [1, 1, 2, 2, 2, 2]
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option = [
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# car 0 1 2 3 4 5
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[ 1, 0, 0, 0, 1, 1], # option 1
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[ 0, 0, 1, 1, 0, 1], # option 2
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[ 1, 0, 0, 0, 1, 0], # option 3
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[ 1, 1, 0, 1, 0, 0], # option 4
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[ 0, 0, 1, 0, 0, 0] # option 5
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]
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capacity = [
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(1,2),
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(2,3),
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(1,3),
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(2,5),
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(1,5)
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]
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optionDemand = [sum([demand[j]*option[i][j] for j in Cars]) \
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for i in Options]
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#
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# declare variables
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#
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slot = [solver.IntVar(0, nbCars-1, "slot[%i]" % i) for i in Slots]
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setup = {}
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for i in Options:
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for j in Slots:
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setup[(i,j)] = solver.IntVar(0, 1, "setup[%i,%i]" % (i,j))
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setup_flat = [setup[i,j] for i in Options for j in Slots]
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#
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# constraints
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#
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for c in Cars:
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b = [solver.IsEqualCstVar(slot[s], c) for s in Slots]
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solver.Add(solver.Sum(b) == demand[c])
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for o in Options:
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for s in range(0, nbSlots-capacity[o][1]+1):
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b = [setup[o,j] for j in range(s, s + capacity[o][1]-1)]
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solver.Add(solver.Sum(b) <= capacity[o][0])
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for o in Options:
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for s in Slots:
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solver.Add(setup[(o,s)] == solver.Element(option[o], slot[s]))
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for o in Options:
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for i in range(optionDemand[o]):
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s_range = range(0, nbSlots - (i+1) * capacity[o][1])
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ss = [setup[o,s] for s in s_range]
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cc = optionDemand[o] - (i+1) * capacity[o][0]
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if len(ss) > 0 and cc >= 0:
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solver.Add(solver.Sum(ss) >= cc)
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#
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# search and result
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#
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db = solver.Phase(slot + setup_flat,
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solver.CHOOSE_FIRST_UNBOUND,
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solver.ASSIGN_MIN_VALUE)
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solver.NewSearch(db)
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num_solutions = 0
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while solver.NextSolution():
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print "slot:%s" % ",".join([str(slot[i].Value()) for i in Slots])
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print "setup:"
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for o in Options:
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print "%i/%i:" % (capacity[o][0], capacity[o][1]),
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for s in Slots:
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print setup[o,s].Value(),
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print
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print
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num_solutions += 1
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if num_solutions >= num_sol:
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break
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solver.EndSearch()
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print
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print "num_solutions:", num_solutions
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print "failures:", solver.Failures()
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print "branches:", solver.Branches()
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print "WallTime:", solver.WallTime()
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num_sol = 3
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if __name__ == '__main__':
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if len(sys.argv) > 1:
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num_sol = string.atoi(sys.argv[1])
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main(num_sol)
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