A (1.4+ϵ)-approximation algorithm for the 2-Max-Duo problem

The maximum duo-preservation string mapping ( Max-Duo ) problem is the complement of the well studied minimum common string partition problem, both of which have applications in many fields including text compression and bioinformatics. k - Max-Duo is the restricted version of Max-Duo , where every...

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Vydáno v:Journal of combinatorial optimization Ročník 40; číslo 3; s. 806 - 824
Hlavní autoři: Chen, Yong, Lin, Guohui, Liu, Tian, Luo, Taibo, Su, Bing, Xu, Yao, Zhang, Peng
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.10.2020
Springer Nature B.V
Témata:
Algorithms
Approximation
Bioinformatics
Combinatorics
Convex and Discrete Geometry
Degree reduction
Mapping
Mathematical analysis
Mathematical Modeling and Industrial Mathematics
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Strings
Theory of Computation
String partition
Duo-preservation string mapping
G.4 Algorithm design and analysis
Independent set
F.2.2 Pattern matching
Approximation algorithm
G.2.1 Combinatorial algorithms
ISSN:1382-6905, 1573-2886
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Shrnutí:The maximum duo-preservation string mapping ( Max-Duo ) problem is the complement of the well studied minimum common string partition problem, both of which have applications in many fields including text compression and bioinformatics. k - Max-Duo is the restricted version of Max-Duo , where every letter of the alphabet occurs at most k times in each of the strings, which is readily reduced into the well known maximum independent set ( MIS ) problem on a graph of maximum degree Δ ≤ 6 ( k - 1 ) . In particular, 2- Max-Duo can then be approximated arbitrarily close to 1.8 using the state-of-the-art approximation algorithm for the MIS problem on bounded-degree graphs. 2- Max-Duo was proved APX-hard and very recently a ( 1.6 + ϵ ) -approximation algorithm was claimed, for any ϵ > 0 . In this paper, we present a vertex-degree reduction technique, based on which, we show that 2- Max-Duo can be approximated arbitrarily close to 1.4.
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ISSN:1382-6905
1573-2886
DOI:10.1007/s10878-020-00621-0