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ortools-clone/ortools/graph/samples/assignment_min_flow.py
Corentin Le Molgat 0863b128c4 Sync Google to Github
2021-10-13 23:17:11 +02:00

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#!/usr/bin/env python3
# Copyright 2010-2021 Google LLC
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# [START program]
"""Linear assignment example."""
# [START import]
from ortools.graph import pywrapgraph
# [END import]
def main():
"""Solving an Assignment Problem with MinCostFlow."""
# [START solver]
# Instantiate a SimpleMinCostFlow solver.
min_cost_flow = pywrapgraph.SimpleMinCostFlow()
# [END solver]
# [START data]
# Define the directed graph for the flow.
start_nodes = [0, 0, 0, 0] + [
1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4
] + [5, 6, 7, 8]
end_nodes = [1, 2, 3, 4] + [5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8
] + [9, 9, 9, 9]
capacities = [1, 1, 1, 1] + [
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
] + [1, 1, 1, 1]
costs = (
[0, 0, 0, 0] +
[90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115] +
[0, 0, 0, 0])
source = 0
sink = 9
tasks = 4
supplies = [tasks, 0, 0, 0, 0, 0, 0, 0, 0, -tasks]
# [END data]
# [START constraints]
# Add each arc.
for i in range(len(start_nodes)):
min_cost_flow.AddArcWithCapacityAndUnitCost(start_nodes[i],
end_nodes[i], capacities[i],
costs[i])
# Add node supplies.
for i in range(len(supplies)):
min_cost_flow.SetNodeSupply(i, supplies[i])
# [END constraints]
# [START solve]
# Find the minimum cost flow between node 0 and node 10.
status = min_cost_flow.Solve()
# [END solve]
# [START print_solution]
if status == min_cost_flow.OPTIMAL:
print('Total cost = ', min_cost_flow.OptimalCost())
print()
for arc in range(min_cost_flow.NumArcs()):
# Can ignore arcs leading out of source or into sink.
if min_cost_flow.Tail(arc) != source and min_cost_flow.Head(
arc) != sink:
# Arcs in the solution have a flow value of 1. Their start and end nodes
# give an assignment of worker to task.
if min_cost_flow.Flow(arc) > 0:
print('Worker %d assigned to task %d. Cost = %d' %
(min_cost_flow.Tail(arc), min_cost_flow.Head(arc),
min_cost_flow.UnitCost(arc)))
else:
print('There was an issue with the min cost flow input.')
print(f'Status: {status}')
# [END print_solution]
if __name__ == '__main__':
main()
# [END program]