2012
DOI: 10.1016/j.cor.2011.02.026
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An improved algorithm for the longest common subsequence problem

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Cited by 34 publications
(35 citation statements)
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“…In this section, we explain how candidate solutions are evaluated and compared. The method used here to evaluate candidate solutions is adapted from Mousavi and Tabataba (2012) where a similar problem, the LCS, was addressed. To evaluate a candidate solution x, we use the probability of R(x)!y, where y is a random string and the strings in R(x) are assumed to be independent in the sense that Prðr i ðxÞ!yÞ ¼ Prðr i ðxÞ!y9r j ðxÞ!yÞ,8i,j A f1,.…”
Section: Evaluation Of Candidate Solutionsmentioning
confidence: 99%
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“…In this section, we explain how candidate solutions are evaluated and compared. The method used here to evaluate candidate solutions is adapted from Mousavi and Tabataba (2012) where a similar problem, the LCS, was addressed. To evaluate a candidate solution x, we use the probability of R(x)!y, where y is a random string and the strings in R(x) are assumed to be independent in the sense that Prðr i ðxÞ!yÞ ¼ Prðr i ðxÞ!y9r j ðxÞ!yÞ,8i,j A f1,.…”
Section: Evaluation Of Candidate Solutionsmentioning
confidence: 99%
“…Its time complexity is polynomial in input size, and its computational cost can be arbitrarily reduced by reducing the beam size. The heuristic function used in the algorithm to evaluate candidate solutions does not suffer from the scalability issue of the heuristic proposed in Mousavi and Tabataba (2012) as an estimation mechanism is used for long strings. While the algorithm is significantly faster than other recent algorithm for the SCS, it yields superior solution quality in most of the cases.…”
Section: Introductionmentioning
confidence: 99%
“…For arbitrary number of sequences, the problem of computing an LCS is NP-hard [28]. As a result a number of heuristic and/or meta-heuristic techniques have also been applied in the literature to solve the LCS problem for arbitrary number of sequences (e.g., [7,31,34,35]). The related problem of global alignment, which is more relevant in computational biology, has also received much attention in the literature.…”
Section: Introductionmentioning
confidence: 99%
“…This implies that the problem can be solved in polynomial time if the number of sequences m is a constant, in particular it can be solved in quadratic time for two sequences. The complexity of the general problem motivates the use of heuristic algorithms and developing fast heuristics for the longest common subsequence problem is still an active research topic [24,26,27]. One heuristic approach employing evolutionary algorithms reports that evolutionary algorithms yield excellent results in practice [13,20].…”
Section: Introductionmentioning
confidence: 99%