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Improved Approximation Algorithm for Convex Recoloring of Trees

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3879))

Abstract

A pair (T,C) of a tree T and a coloring C is called a colored tree. Given a colored tree (T,C) any coloring C′ of T is called a recoloring of T. Given a weight function on the vertices of the tree the recoloring distance of a recoloring is the total weight of recolored vertices. A coloring of a tree is convex if for any two vertices u and v that are colored by the same color c, every vertex on the path from u to v is also colored by c. In the minimum convex recoloring problem we are given a colored tree and a weight function and our goal is to find a convex recoloring of minimum recoloring distance.

The minimum convex recoloring problem naturally arises in the context of phylogenetic trees. Given a set of related species the goal of phylogenetic reconstruction is to construct a tree that would best describe the evolution of this set of species. In this context a convex coloring correspond to perfect phylogeny. Since perfect phylogeny is not always possible the next best thing is to find a tree which is as close to convex as possible, or, in other words, a tree with minimum recoloring distance.

We present a (2+ε)-approximation algorithm for the minimum convex recoloring problem, whose running time is O(n 2 + n(1/ε)2 41/ε). This result improves the previously known 3-approximation algorithm for this NP-hard problem.

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© 2006 Springer-Verlag Berlin Heidelberg

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Bar-Yehuda, R., Feldman, I., Rawitz, D. (2006). Improved Approximation Algorithm for Convex Recoloring of Trees. In: Erlebach, T., Persinao, G. (eds) Approximation and Online Algorithms. WAOA 2005. Lecture Notes in Computer Science, vol 3879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11671411_5

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  • DOI: https://doi.org/10.1007/11671411_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32207-8

  • Online ISBN: 978-3-540-32208-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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