110 lines
3.6 KiB
Python
110 lines
3.6 KiB
Python
# Copyright 2010-2017 Google
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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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from __future__ import print_function
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from ortools.sat.python import cp_model
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def main():
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# Data.
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cost = [[90, 76, 75, 70, 50, 74],
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[35, 85, 55, 65, 48, 101],
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[125, 95, 90, 105, 59, 120],
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[45, 110, 95, 115, 104, 83],
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[60, 105, 80, 75, 59, 62],
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[45, 65, 110, 95, 47, 31],
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[38, 51, 107, 41, 69, 99],
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[47, 85, 57, 71, 92, 77],
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[39, 63, 97, 49, 118, 56],
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[47, 101, 71, 60, 88, 109],
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[17, 39, 103, 64, 61, 92],
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[101, 45, 83, 59, 92, 27]]
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group1 = [[0, 0, 1, 1], # Workers 2, 3
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[0, 1, 0, 1], # Workers 1, 3
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[0, 1, 1, 0], # Workers 1, 2
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[1, 1, 0, 0], # Workers 0, 1
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[1, 0, 1, 0]] # Workers 0, 2
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group2 = [[0, 0, 1, 1], # Workers 6, 7
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[0, 1, 0, 1], # Workers 5, 7
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[0, 1, 1, 0], # Workers 5, 6
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[1, 1, 0, 0], # Workers 4, 5
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[1, 0, 0, 1]] # Workers 4, 7
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group3 = [[0, 0, 1, 1], # Workers 10, 11
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[0, 1, 0, 1], # Workers 9, 11
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[0, 1, 1, 0], # Workers 9, 10
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[1, 0, 1, 0], # Workers 8, 10
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[1, 0, 0, 1]] # Workers 8, 11
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sizes = [10, 7, 3, 12, 15, 4, 11, 5]
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total_size_max = 15
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num_workers = len(cost)
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num_tasks = len(cost[1])
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all_workers = range(num_workers)
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all_tasks = range(num_tasks)
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# Model.
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model = cp_model.CpModel()
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# Variables
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total_cost = model.NewIntVar(0, 1000, 'total_cost')
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x = [[model.NewBoolVar('x[%i,%i]' % (i, j)) for j in all_tasks]
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for i in all_workers]
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works = [model.NewBoolVar('works[%i]' % i) for i in all_workers]
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# Constraints
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# Link x and workers.
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for i in range(num_workers):
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model.AddMaxEquality(works[i], x[i])
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# Each task is assigned to at least one worker.
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[model.Add(sum(x[i][j] for i in all_workers) >= 1) for j in all_tasks]
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# Total task size for each worker is at most total_size_max
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for i in all_workers:
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model.Add(sum(sizes[j] * x[i][j] for j in all_tasks) <= total_size_max)
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# Group constraints.
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model.AddAllowedAssignments([works[0], works[1], works[2], works[3]], group1)
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model.AddAllowedAssignments([works[4], works[5], works[6], works[7]], group2)
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model.AddAllowedAssignments([works[8], works[9], works[10], works[11]], group3)
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# Total cost
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model.Add(total_cost ==
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sum(x[i][j] * cost[i][j] for j in all_tasks for i in all_workers))
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model.Minimize(total_cost)
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solver = cp_model.CpSolver()
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status = solver.Solve(model)
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if status == cp_model.OPTIMAL:
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print('Total cost = %i' % solver.ObjectiveValue())
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print()
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for i in all_workers:
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for j in all_tasks:
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if solver.Value(x[i][j]) == 1:
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print('Worker ', i, ' assigned to task ', j, ' Cost = ', cost[i][j])
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print()
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print('Statistics')
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print(' - conflicts : %i' % solver.NumConflicts())
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print(' - branches : %i' % solver.NumBranches())
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print(' - wall time : %f ms' % solver.WallTime())
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if __name__ == '__main__':
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main()
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