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This algorithm was first published by Joseph Kruskal in 1956, [3] and was rediscovered soon afterward by Loberman & Weinberger (1957). [4] Other algorithms for this problem include Prim's algorithm, Borůvka's algorithm, and the reverse-delete algorithm.
Other well-known algorithms for this problem include Kruskal's algorithm and Borůvka's algorithm. [8] These algorithms find the minimum spanning forest in a possibly disconnected graph; in contrast, the most basic form of Prim's algorithm only finds minimum spanning trees in connected graphs.
Similarly to Prim's algorithm there are components in Kruskal's approach that can not be parallelised in its classical variant. For example, determining whether or not two vertices are in the same subtree is difficult to parallelise, as two union operations might attempt to join the same subtrees at the same time.
For example, Kruskal's algorithm processes edges in turn, deciding whether to include the edge in the MST based on whether it would form a cycle with all previously chosen edges. Both Prim's algorithm and Kruskal's algorithm require processes to know the state of the whole graph, which is very difficult to discover in the message-passing model.
All the above algorithms have biases of various sorts: depth-first search is biased toward long corridors, while Kruskal's/Prim's algorithms are biased toward many short dead ends. Wilson's algorithm, [1] on the other hand, generates an unbiased sample from the uniform distribution over all mazes, using loop-erased random walks.
Such a tree can be found with algorithms such as Prim's or Kruskal's after multiplying the edge weights by -1 and solving the MST problem on the new graph. A path in the maximum spanning tree is the widest path in the graph between its two endpoints: among all possible paths, it maximizes the weight of the minimum-weight edge. [ 21 ]
[2] [3] It combines the design paradigms of divide and conquer algorithms, greedy algorithms, and randomized algorithms to achieve expected linear performance. Deterministic algorithms that find the minimum spanning tree include Prim's algorithm, Kruskal's algorithm, reverse-delete algorithm, and Borůvka's algorithm.
These algorithms can be made to take time () on complete graphs, unlike another common choice, Kruskal's algorithm, which is slower because it involves sorting all distances. [13] For points in low-dimensional spaces, the problem may be solved more quickly, as detailed below.