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Edmonds' algorithm

Algorithm for the directed version of the minimum spanning tree problem

In graph theory, Edmonds' algorithm or Chu-Liu/Edmonds' algorithm is an algorithm for finding a spanning arborescence of minimum weight (sometimes called an optimum branching). It is the directed analog of the minimum spanning tree problem. The algorithm was proposed independently first by Yoeng-Jin Chu and Tseng-Hong Liu (1965) and then by Jack Edmonds (1967).

01Algorithm

Description

The algorithm takes as input a directed graph D=\langle V,E\rangle where V is the set of nodes and E is the set of directed edges, a distinguished vertex r\in V called the root, and a real-valued weight w(e) for each edge e\in E. It returns a spanning arborescence A rooted at r of minimum weight, where the weight of an arborescence is defined to be the sum of its edge weights, w(A)=\sum _{e\in A}{w(e)}.

The algorithm has a recursive description. Let f(D,r,w) denote the function which returns a spanning arborescence rooted at r of minimum weight. We first remove any edge from E whose destination is r. We may also replace any set of parallel edges (edges between the same pair of vertices in the same direction) by a single edge with weight equal to the minimum of the weights of these parallel edges.

Now, for each node v other than the root, find the edge incoming to v of lowest weight (with ties broken arbitrarily). Denote the source of this edge by \pi (v). If the set of edges P=\{(\pi (v),v)\mid v\in V\setminus \{r\}\} does not contain any cycles, then f(D,r,w)=P.

Otherwise, P contains at least one cycle. Arbitrarily choose one of these cycles and call it C. We now define a new weighted directed graph D^{\prime }=\langle V^{\prime },E^{\prime }\rangle in which the cycle C is "contracted" into one node as follows:

The nodes of V^{\prime } are the nodes of V not in C plus a new node denoted v_{C}.

  • If (u,v) is an edge in E with u\notin C and v\in C (an edge coming into the cycle), then include in E^{\prime } a new edge e=(u,v_{C}), and define w^{\prime }(e)=w(u,v)-w(\pi (v),v).
  • If (u,v) is an edge in E with u\in C and v\notin C (an edge going away from the cycle), then include in E^{\prime } a new edge e=(v_{C},v), and define w^{\prime }(e)=w(u,v).
  • If (u,v) is an edge in E with u\notin C and v\notin C (an edge unrelated to the cycle), then include in E^{\prime } a new edge e=(u,v), and define w^{\prime }(e)=w(u,v).

For each edge in E^{\prime }, we remember which edge in E it corresponds to.

Now find a minimum spanning arborescence A^{\prime } of D^{\prime } using a call to f(D^{\prime },r,w^{\prime }). Since A^{\prime } is a spanning arborescence, each vertex has exactly one incoming edge. Let (u,v_{C}) be the unique incoming edge to v_{C} in A^{\prime }. This edge corresponds to an edge (u,v)\in E with v\in C. Remove the edge (\pi (v),v) from C, breaking the cycle. Mark each remaining edge in C. For each edge in A^{\prime }, mark its corresponding edge in E. Now we define f(D,r,w) to be the set of marked edges, which form a minimum spanning arborescence.

Observe that f(D,r,w) is defined in terms of f(D^{\prime },r,w^{\prime }), with D^{\prime } having strictly fewer vertices than D. Finding f(D,r,w) for a single-vertex graph is trivial (it is just D itself), so the recursive algorithm is guaranteed to terminate.

02Running time

The running time of this algorithm is O(EV). A faster implementation of the algorithm due to Robert Tarjan runs in time O(E\log V) for sparse graphs and O(V^{2}) for dense graphs. This is as fast as Prim's algorithm for an undirected minimum spanning tree. In 1986, Gabow, Galil, Spencer, and Tarjan produced a faster implementation, with running time O(E+V\log V).

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Sources and credits

This article is adapted from the Wikipedia article Edmonds' algorithm, written by its contributors and licensed under CC BY-SA 4.0. Fathomly has changed the layout, removed citation markers, navigation and maintenance notices, and adjusted punctuation. This adapted version is shared under the same license. For references, see the original article.

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