Back to Search Start Over

Exact algorithms for the repetition-bounded longest common subsequence problem.

Authors :
Asahiro, Yuichi
Jansson, Jesper
Lin, Guohui
Miyano, Eiji
Ono, Hirotaka
Utashima, Tadatoshi
Source :
Theoretical Computer Science. Oct2020, Vol. 838, p238-249. 12p.
Publication Year :
2020

Abstract

• Bounded-Repetition Longest Common Subsequence problem is introduced. • Exact, exponential-time algorithms are presented. • NP-hardness and APX-hardness results for the problem on restricted instances are shown. In this paper, we study exact, exponential-time algorithms for a variant of the classic Longest Common Subsequence problem called the Repetition-Bounded Longest Common Subsequence problem (or RBLCS , for short): Let an alphabet S be a finite set of symbols and an occurrence constraint C o c c be a function C o c c : S → N , assigning an upper bound on the number of occurrences of each symbol in S. Given two sequences X and Y over the alphabet S and an occurrence constraint C o c c , the goal of RBLCS is to find a longest common subsequence of X and Y such that each symbol s ∈ S appears at most C o c c (s) times in the obtained subsequence. The special case where C o c c (s) = 1 for every symbol s ∈ S is known as the Repetition-Free Longest Common Subsequence problem (RFLCS) and has been studied previously; e.g., in [1] , Adi et al. presented a simple (exponential-time) exact algorithm for RFLCS. However, they did not analyze its time complexity in detail, and to the best of our knowledge, there are no previous results on the running times of any exact algorithms for this problem. Without loss of generality, we will assume that | X | ≤ | Y | and | X | = n. In this paper, we first propose a simpler algorithm for RFLCS based on the strategy used in [1] and show explicitly that its running time is O (1.44225 n). Next, we provide a dynamic programming (DP) based algorithm for RBLCS and prove that its running time is O (1.44225 n) for any occurrence constraint C o c c , and even less in certain special cases. In particular, for RFLCS , our DP-based algorithm runs in O (1.41422 n) time, which is faster than the previous one. Furthermore, we prove NP-hardness and APX-hardness results for RBLCS on restricted instances. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
*ALGORITHMS
*DYNAMIC programming

Details

Language :
English
ISSN :
03043975
Volume :
838
Database :
Academic Search Index
Journal :
Theoretical Computer Science
Publication Type :
Academic Journal
Accession number :
145414040
Full Text :
https://doi.org/10.1016/j.tcs.2020.07.042