125 lines
3.5 KiB
Python
125 lines
3.5 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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Assignment problem in Google CP Solver.
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Winston 'Operations Research', Assignment Problems, page 393f
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(generalized version with added test column)
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Compare with the following models:
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* Comet : http://www.hakank.org/comet/assignment.co
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* ECLiPSE : http://www.hakank.org/eclipse/assignment.ecl
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* Gecode : http://www.hakank.org/gecode/assignment.cpp
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* MiniZinc: http://www.hakank.org/minizinc/assignment.mzn
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* Tailor/Essence': http://www.hakank.org/tailor/assignment.eprime
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* SICStus: http://hakank.org/sicstus/assignment.pl
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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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from ortools.constraint_solver import pywrapcp
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def main(cost, rows, cols):
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# Create the solver.
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solver = pywrapcp.Solver('n-queens')
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#
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# data
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#
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# declare variables
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total_cost = solver.IntVar(0, 100, 'total_cost')
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x = []
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for i in range(rows):
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t = []
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for j in range(cols):
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t.append(solver.IntVar(0,1, 'x[%i,%i]'%(i,j)))
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x.append(t)
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x_flat = [x[i][j] for i in range(rows) for j in range(cols)]
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#
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# constraints
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#
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# total_cost
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solver.Add(total_cost == solver.Sum([solver.ScalProd(x_row, cost_row) for (x_row, cost_row) in zip(x, cost)]))
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# exacly one assignment per row, all rows must be assigned
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[solver.Add(solver.Sum([x[row][j] for j in range(cols)]) == 1) for row in range(rows)]
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# zero or one assignments per column
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[solver.Add(solver.Sum([x[i][col] for i in range(rows)]) <= 1) for col in range(cols)]
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objective = solver.Minimize(total_cost, 1)
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#
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# solution and search
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#
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solution = solver.Assignment()
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solution.Add(x_flat)
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solution.Add(total_cost)
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# db: DecisionBuilder
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db = solver.Phase(x_flat,
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solver.INT_VAR_SIMPLE,
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solver.ASSIGN_MIN_VALUE)
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solver.NewSearch(db,[objective])
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num_solutions = 0
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while solver.NextSolution():
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print "total_cost:", total_cost.Value()
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for i in range(rows):
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for j in range(cols):
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print x[i][j].Value(),
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print
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print
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for i in range(rows):
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print "Task:",i,
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for j in range(cols):
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if x[i][j].Value() == 1:
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print " is done by ", j
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print
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num_solutions += 1
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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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# Problem instance
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# hakank: I added the fifth column to make it more
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# interesting
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rows = 4
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cols = 5
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cost = [[14, 5, 8, 7, 15],
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[ 2, 12, 6, 5, 3],
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[ 7, 8, 3, 9, 7],
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[ 2, 4, 6, 10, 1]
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]
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if __name__ == '__main__':
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main(cost, rows, cols)
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