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An Optimal Minimum Spanning Tree Algorithm

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1853))

Abstract

We establish that the algorithmic complexity of the minimum spanning tree problem is equal to its decision-tree complexity. Specifically, we present a deterministic algorithm to find a minimum spanning forest of a graph with n vertices and m edges that runs in time O(T(m,n)) where T is the minimum number of edge-weight comparisons needed to determine the solution. The algorithm is quite simple and can be implemented on a pointer machine.

Although our time bound is optimal, the exact function describing it is not known at present. The current best bounds known for T are T(m,n)=Ω(m) and T(m,n)=O(itm·α(m,n)), where α is a certain natural inverse of Ackermann’s function.

Even under the assumption that T is super-linear, we show that if the input graph is selected from G n,m, our algorithm runs in linear time w.h.p., regardless of n, m, or the permutation of edge weights. The analysis uses a new martingale for G n,m similar to the edge-exposure martingale for G n,p.

Part of this work was supported by Texas Advanced Research Program Grant 003658-0029-1999. Seth Pettie was also supported by an MCD Fellowship.

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Pettie, S., Ramachandran, V. (2000). An Optimal Minimum Spanning Tree Algorithm. In: Montanari, U., Rolim, J.D.P., Welzl, E. (eds) Automata, Languages and Programming. ICALP 2000. Lecture Notes in Computer Science, vol 1853. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45022-X_6

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  • DOI: https://doi.org/10.1007/3-540-45022-X_6

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67715-4

  • Online ISBN: 978-3-540-45022-1

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