sfas 0.0.4

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Small Feedback Arc Set (sfas)

Efficient implementation of a greedy algorithm for computing small feedback arc sets in directed weighted multi-graphs. This implementation is an adaptation of the algorithm described in Section 2.3 of this article, with additional generalization to support weights and parallel edges.

Description

Given a weighted directed graph, calculates linear arrangement of the nodes that minimizes (greedily) the number of backward edges (feedback arc set). In particular, removing the set of edges going backward in the resulting order breaks all directed cycles in the graph.

Interface

Input:

1. connections: list of edges, each represented as a 3-item list consisting of [, , ]
2. verbosity: prints progress and other stats for values >0
3. random_seed: randomness is in picking the next "greedy" step among equally qualified ones

Output:

1. list with all nodes, ordered so that the total weight of edges going backwards (w.r.t. this order) is small

Install

pip install sfas

Example usage

from sfas import greedy

graph = [
    ['a', 'b', 1],
    ['b', 'c', 1],
    ['c', 'a', 2],
]
greedy.compute_order(graph, verbosity=0, random_seed=0)

output

['c', 'a', 'b']

Questions / suggestions welcome

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