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License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CPM.2019.5
URN: urn:nbn:de:0030-drops-104769
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2019/10476/
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Jiang, Haitao ; Guo, Jiong ; Zhu, Daming ; Zhu, Binhai

A 2-Approximation Algorithm for the Complementary Maximal Strip Recovery Problem

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LIPIcs-CPM-2019-5.pdf (0.5 MB)

Abstract

The Maximal Strip Recovery problem (MSR) and its complementary (CMSR) are well-studied NP-hard problems in computational genomics. The input of these dual problems are two signed permutations. The goal is to delete some gene markers from both permutations, such that, in the remaining permutations, each gene marker has at least one common neighbor. Equivalently, the resulting permutations could be partitioned into common strips of length at least two. Then MSR is to maximize the number of remaining genes, while the objective of CMSR is to delete the minimum number of gene markers. In this paper, we present a new approximation algorithm for the Complementary Maximal Strip Recovery (CMSR) problem. Our approximation factor is 2, improving the currently best 7/3-approximation algorithm. Although the improvement on the factor is not huge, the analysis is greatly simplified by a compensating method, commonly referred to as the non-oblivious local search technique. In such a method a substitution may not always increase the value of the current solution (it sometimes may even decrease the solution value), though it always improves the value of another function seemingly unrelated to the objective function.

BibTeX - Entry

@InProceedings{jiang_et_al:LIPIcs:2019:10476,
  author =	{Haitao Jiang and Jiong Guo and Daming Zhu and Binhai Zhu},
  title =	{{A 2-Approximation Algorithm for the Complementary Maximal Strip Recovery Problem}},
  booktitle =	{30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019)},
  pages =	{5:1--5:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-103-0},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{128},
  editor =	{Nadia Pisanti and Solon P. Pissis},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2019/10476},
  URN =		{urn:nbn:de:0030-drops-104769},
  doi =		{10.4230/LIPIcs.CPM.2019.5},
  annote =	{Keywords: Maximal strip recovery, complementary maximal strip recovery, computational genomics, approximation algorithm, local search}
}

Keywords: Maximal strip recovery, complementary maximal strip recovery, computational genomics, approximation algorithm, local search
Collection: 30th Annual Symposium on Combinatorial Pattern Matching (CPM 2019)
Issue Date: 2019
Date of publication: 06.06.2019

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