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+--- Thread: Reproducing assignment with min cost flow in networkx (/thread-19113.html)
Reproducing assignment with min cost flow in networkx - mntfr - Jun-13-2019
Hi so I have seen the ortools webpage ortools where it states that you can solve the assignment problem with the min cost flow algorithm, however when I try to reproduce this process with networkx I get an error. Can somebody point me to what am I doing wrong?
workersList = ['s1', 's2', 's3', 's4']
tasksList = ['c1', 'c2', 'c3', 'c4']
costs = [[90, 76, 75, 70], [35, 85, 55, 65], [125, 95, 90, 105], [45, 110, 95, 115]]
import networkx as nx
G = nx.DiGraph()
G.add_node('Start', demand = len(workersList))
G.add_node('End', demand = -len(workersList))
G.add_nodes_from(workersList)
G.add_nodes_from(tasksList)
for worker in workersList:
G.add_edge('Start', work, weight=0, capacity=1)
for task in tasksList:
G.add_edge(task, 'End', weigth=0, capacity=1)
for i, worker in enumerate(workersList):
for j, task in enumerate(tasksList):
if costs[i][j] != 'NA':
G.add_edge(worker, task, weight=costs[i][j], capacity=1)
flowDict = nx.min_cost_flow(G)
print(flowDict)