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Heuristic algorithms for the Longest Filled Common Subsequence Problem

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At CPM 2017, Castelli et al. define and study a new variant of the Longest Common Subsequence Problem, termed the Longest Filled Common Subsequence Problem (LFCS). For the LFCS problem, the input consists of two strings $A$ and $B$ and a multiset of characters $\mathcal{M}$. The goal is to insert the characters from $\mathcal{M}$ into the string $B$, thus obtaining a new string $B^*$, such that the Longest Common Subsequence (LCS) between $A$ and $B^*$ is maximized. Casteli et al. show that the problem is NP-hard and provide a 3/5-approximation algorithm for the problem. In this paper we study the problem from the experimental point of view. We introduce, implement and test new heuristic algorithms and compare them with the approximation algorithm of Casteli et al. Moreover, we introduce an Integer Linear Program (ILP) model for the problem and we use the state of the art ILP solver, Gurobi, to obtain exact solution for moderate sized instances.

Radu Stefan Mincu, Alexandru Popa (1 and 2) __INSTITUTION_2__ University of Bucharest, Romania, (2) National Institute for Research, Development in Informatics, Bucharest, Romania)• 2019

Related benchmarks

TaskDatasetResultRank
Longest Functional Common Subsequence (LFCS)SMALL literature instances
LFCS Objective Score67.87
90
Longest Common SubsequenceLarge
Average Solution Quality918.1
72
OptimizationSongs (rem=0.6)
Objective Value144
48
Song identificationSONGS (rem = 0.8)
Identification Score (obj)107
48
Song identificationSongs (rem=0.4)
Object Count181
48
Song identificationSongs (rem = 0.2)
Objective Value217
48
Song identificationSONGS 0.0
Object Count248
48
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