# Copyright 2010-2018 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. """MaxFlow and MinCostFlow examples.""" from __future__ import print_function from ortools.graph import pywrapgraph def MaxFlow(): """MaxFlow simple interface example.""" print('MaxFlow on a simple network.') tails = [0, 0, 0, 0, 1, 2, 3, 3, 4] heads = [1, 2, 3, 4, 3, 4, 4, 5, 5] capacities = [5, 8, 5, 3, 4, 5, 6, 6, 4] expected_total_flow = 10 max_flow = pywrapgraph.SimpleMaxFlow() for i in range(0, len(tails)): max_flow.AddArcWithCapacity(tails[i], heads[i], capacities[i]) if max_flow.Solve(0, 5) == max_flow.OPTIMAL: print('Total flow', max_flow.OptimalFlow(), '/', expected_total_flow) for i in range(max_flow.NumArcs()): print(('From source %d to target %d: %d / %d' % (max_flow.Tail(i), max_flow.Head(i), max_flow.Flow(i), max_flow.Capacity(i)))) print('Source side min-cut:', max_flow.GetSourceSideMinCut()) print('Sink side min-cut:', max_flow.GetSinkSideMinCut()) else: print('There was an issue with the max flow input.') def MinCostFlow(): """MinCostFlow simple interface example. Note that this example is actually a linear sum assignment example and will be more efficiently solved with the pywrapgraph.LinearSumAssignement class. """ print('MinCostFlow on 4x4 matrix.') num_sources = 4 num_targets = 4 costs = [[90, 75, 75, 80], [35, 85, 55, 65], [125, 95, 90, 105], [45, 110, 95, 115]] expected_cost = 275 min_cost_flow = pywrapgraph.SimpleMinCostFlow() for source in range(0, num_sources): for target in range(0, num_targets): min_cost_flow.AddArcWithCapacityAndUnitCost( source, num_sources + target, 1, costs[source][target]) for node in range(0, num_sources): min_cost_flow.SetNodeSupply(node, 1) min_cost_flow.SetNodeSupply(num_sources + node, -1) status = min_cost_flow.Solve() if status == min_cost_flow.OPTIMAL: print('Total flow', min_cost_flow.OptimalCost(), '/', expected_cost) for i in range(0, min_cost_flow.NumArcs()): if min_cost_flow.Flow(i) > 0: print('From source %d to target %d: cost %d' % (min_cost_flow.Tail(i), min_cost_flow.Head(i) - num_sources, min_cost_flow.UnitCost(i))) else: print('There was an issue with the min cost flow input.') def main(): MaxFlow() MinCostFlow() if __name__ == '__main__': main()