111 lines
3.1 KiB
Python
Executable File
111 lines
3.1 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright 2010-2022 Google LLC
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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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# [START program]
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"""Solve a simple assignment problem."""
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# [START import]
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from ortools.sat.python import cp_model
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# [END import]
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def main():
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# Data
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# [START data]
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costs = [
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[90, 76, 75, 70],
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[35, 85, 55, 65],
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[125, 95, 90, 105],
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[45, 110, 95, 115],
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[60, 105, 80, 75],
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[45, 65, 110, 95],
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]
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num_workers = len(costs)
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num_tasks = len(costs[0])
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team1 = [0, 2, 4]
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team2 = [1, 3, 5]
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# Maximum total of tasks for any team
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team_max = 2
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# [END data]
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# Model
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# [START model]
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model = cp_model.CpModel()
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# [END model]
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# Variables
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# [START variables]
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x = {}
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for worker in range(num_workers):
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for task in range(num_tasks):
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x[worker, task] = model.NewBoolVar(f'x[{worker},{task}]')
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# [END variables]
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# Constraints
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# [START constraints]
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# Each worker is assigned to at most one task.
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for worker in range(num_workers):
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model.AddAtMostOne(x[worker, task] for task in range(num_tasks))
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# Each task is assigned to exactly one worker.
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for task in range(num_tasks):
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model.AddExactlyOne(x[worker, task] for worker in range(num_workers))
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# Each team takes at most two tasks.
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team1_tasks = []
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for worker in team1:
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for task in range(num_tasks):
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team1_tasks.append(x[worker, task])
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model.Add(sum(team1_tasks) <= team_max)
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team2_tasks = []
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for worker in team2:
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for task in range(num_tasks):
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team2_tasks.append(x[worker, task])
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model.Add(sum(team2_tasks) <= team_max)
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# [END constraints]
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# Objective
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# [START objective]
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objective_terms = []
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for worker in range(num_workers):
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for task in range(num_tasks):
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objective_terms.append(costs[worker][task] * x[worker, task])
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model.Minimize(sum(objective_terms))
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# [END objective]
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# Solve
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# [START solve]
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solver = cp_model.CpSolver()
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status = solver.Solve(model)
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# [END solve]
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# Print solution.
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# [START print_solution]
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if status == cp_model.OPTIMAL or status == cp_model.FEASIBLE:
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print(f'Total cost = {solver.ObjectiveValue()}\n')
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for worker in range(num_workers):
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for task in range(num_tasks):
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if solver.BooleanValue(x[worker, task]):
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print(f'Worker {worker} assigned to task {task}.' +
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f' Cost = {costs[worker][task]}')
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else:
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print('No solution found.')
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# [END print_solution]
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if __name__ == '__main__':
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main()
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# [END program]
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