Local search for string problems: Brute force is essentially optimal

Jiong Guo, Danny Hermelin, Christian Komusiewicz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

We address the problem of whether the brute-force procedure for the local improvement step in a local search algorithm can be substantially improved when applied to classical NP-hard string problems. We examine four problems in this domain: Closest String, Longest Common Subsequence, Shortest Common Supersequence, and Shortest Common Superstring. Herein, we consider arguably the most fundamental string distance measure, namely the Hamming distance, which has been applied in practical local search implementations for string problems. Our results indicate that for all four problems, the brute-force algorithm is essentially optimal.

Original languageEnglish
Title of host publicationCombinatorial Pattern Matching - 24th Annual Symposium, CPM 2013, Proceedings
Pages130-141
Number of pages12
DOIs
StatePublished - 24 Sep 2013
Event24th Annual Symposium on Combinatorial Pattern Matching, CPM 2013 - Bad Herrenalb, Germany
Duration: 17 Jun 201319 Jun 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7922 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference24th Annual Symposium on Combinatorial Pattern Matching, CPM 2013
Country/TerritoryGermany
CityBad Herrenalb
Period17/06/1319/06/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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