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.2017.3
URN: urn:nbn:de:0030-drops-73483
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Mucha, Marcin

Shortest Superstring

LIPIcs-CPM-2017-3.pdf (0.2 MB)


In the Shortest Superstring problem (SS) one has to find a shortest string s containing given strings s_1,...,s_n as substrings. The problem is NP-hard, so a natural question is that of its approximability.

One natural approach to approximately solving SS is the following GREEDY heuristic: repeatedly merge two strings with the largest overlap until only a single string is left. This heuristic is conjectured to be a 2-approximation, but even after 30 years since the conjecture has been posed, we are still very far from proving it. The situation is better for non-greedy approximation algorithms, where several approaches yielding 2.5-approximation (and better) are known.

In this talk, we will survey the main results in the area, focusing on the fundamental ideas and intuitions.

BibTeX - Entry

  author =	{Marcin Mucha},
  title =	{{Shortest Superstring}},
  booktitle =	{28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017)},
  pages =	{3:1--3:1},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-039-2},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{78},
  editor =	{Juha K{\"a}rkk{\"a}inen and Jakub Radoszewski and Wojciech Rytter},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-73483},
  doi =		{10.4230/LIPIcs.CPM.2017.3},
  annote =	{Keywords: shortest superstring, approximation algorithms}

Keywords: shortest superstring, approximation algorithms
Collection: 28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017)
Issue Date: 2017
Date of publication: 30.06.2017

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