111 lines
2.7 KiB
Python
111 lines
2.7 KiB
Python
# Copyright 2011 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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Knapsack problem using MIP in Google or-tools.
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From the OPL model knapsack.mod
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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:
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http://www.hakank.org/google_or_tools/
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"""
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import sys
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from ortools.linear_solver import pywraplp
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def main(sol='GLPK'):
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# Create the solver.
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print 'Solver: ', sol
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# using GLPK
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if sol == 'GLPK':
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solver = pywraplp.Solver('CoinsGridGLPK',
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pywraplp.Solver.GLPK_MIXED_INTEGER_PROGRAMMING)
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else:
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# Using CLP
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solver = pywraplp.Solver('CoinsGridCLP',
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pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)
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#
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# data
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#
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nb_items = 12
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nb_resources = 7
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items = range(nb_items)
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resources = range(nb_resources)
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capacity = [18209, 7692, 1333, 924, 26638, 61188, 13360]
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value = [96, 76, 56, 11, 86, 10, 66, 86, 83, 12, 9, 81]
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use = [[19, 1, 10, 1, 1, 14, 152, 11, 1, 1, 1, 1],
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[0, 4, 53, 0, 0, 80, 0, 4, 5, 0, 0, 0],
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[4, 660, 3, 0, 30, 0, 3, 0, 4, 90, 0, 0],
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[7, 0, 18, 6, 770, 330, 7, 0, 0, 6, 0, 0],
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[0, 20, 0, 4, 52, 3, 0, 0, 0, 5, 4, 0],
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[0, 0, 40, 70, 4, 63, 0, 0, 60, 0, 4, 0],
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[0, 32, 0, 0, 0, 5, 0, 3, 0, 660, 0, 9]]
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max_value = max(capacity)
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#
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# variables
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#
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take = [solver.IntVar(0, max_value, 'take[%i]' % j) for j in items]
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# total cost, to be maximized
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z = solver.Sum([value[i] * take[i] for i in items])
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#
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# constraints
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#
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for r in resources:
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solver.Add(solver.Sum([use[r][i] * take[i]
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for i in items]) <= capacity[r])
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# objective
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objective = solver.Maximize(z)
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#
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# solution and search
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#
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solver.Solve()
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print
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print 'z: ', int(solver.Objective().Value())
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print 'take:',
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for i in items:
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print int(take[i].SolutionValue()),
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print
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print
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print 'walltime :', solver.WallTime(), 'ms'
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if sol == 'CBC':
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print 'iterations:', solver.Iterations()
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if __name__ == '__main__':
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sol = 'GLPK'
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if len(sys.argv) > 1:
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sol = sys.argv[1]
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if sol != 'GLPK' and sol != 'CBC':
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print 'Solver must be either GLPK or CBC'
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sys.exit(1)
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main(sol)
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