77 lines
2.3 KiB
Python
Executable File
77 lines
2.3 KiB
Python
Executable File
#!/usr/bin/env python3
|
|
# Copyright 2010-2025 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]
|
|
"""Solve assignment problem using linear assignment solver."""
|
|
# [START import]
|
|
import numpy as np
|
|
|
|
from ortools.graph.python import linear_sum_assignment
|
|
|
|
# [END import]
|
|
|
|
|
|
def main():
|
|
"""Linear Sum Assignment example."""
|
|
# [START solver]
|
|
assignment = linear_sum_assignment.SimpleLinearSumAssignment()
|
|
# [END solver]
|
|
|
|
# [START data]
|
|
costs = np.array(
|
|
[
|
|
[90, 76, 75, 70],
|
|
[35, 85, 55, 65],
|
|
[125, 95, 90, 105],
|
|
[45, 110, 95, 115],
|
|
]
|
|
)
|
|
|
|
# Let's transform this into 3 parallel vectors (start_nodes, end_nodes,
|
|
# arc_costs)
|
|
end_nodes_unraveled, start_nodes_unraveled = np.meshgrid(
|
|
np.arange(costs.shape[1]), np.arange(costs.shape[0])
|
|
)
|
|
start_nodes = start_nodes_unraveled.ravel()
|
|
end_nodes = end_nodes_unraveled.ravel()
|
|
arc_costs = costs.ravel()
|
|
# [END data]
|
|
|
|
# [START constraints]
|
|
assignment.add_arcs_with_cost(start_nodes, end_nodes, arc_costs)
|
|
# [END constraints]
|
|
|
|
# [START solve]
|
|
status = assignment.solve()
|
|
# [END solve]
|
|
|
|
# [START print_solution]
|
|
if status == assignment.OPTIMAL:
|
|
print(f"Total cost = {assignment.optimal_cost()}\n")
|
|
for i in range(0, assignment.num_nodes()):
|
|
print(
|
|
f"Worker {i} assigned to task {assignment.right_mate(i)}."
|
|
+ f" Cost = {assignment.assignment_cost(i)}"
|
|
)
|
|
elif status == assignment.INFEASIBLE:
|
|
print("No assignment is possible.")
|
|
elif status == assignment.POSSIBLE_OVERFLOW:
|
|
print("Some input costs are too large and may cause an integer overflow.")
|
|
# [END print_solution]
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|
|
# [END Program]
|