ACM Transactions on Database Systems (TODS)
Data compression: methods and theory
Data compression: methods and theory
Sparse dynamic programming II: convex and concave cost functions
Journal of the ACM (JACM)
On the Approximation of Shortest Common Supersequencesand Longest Common Subsequences
SIAM Journal on Computing
The Complexity of Some Problems on Subsequences and Supersequences
Journal of the ACM (JACM)
A linear space algorithm for computing maximal common subsequences
Communications of the ACM
Experimenting an approximation algorithm for the LCS
Discrete Applied Mathematics
Data Structures and Algorithms
Data Structures and Algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
A Survey of Longest Common Subsequence Algorithms
SPIRE '00 Proceedings of the Seventh International Symposium on String Processing Information Retrieval (SPIRE'00)
Area-efficient instruction set synthesis for reconfigurable system-on-chip designs
Proceedings of the 41st annual Design Automation Conference
A large neighborhood search heuristic for the longest common subsequence problem
Journal of Heuristics
Finding the longest common subsequence for multiple biological sequences by ant colony optimization
Computers and Operations Research
Beam search for the longest common subsequence problem
Computers and Operations Research
Probabilistic beam search for the longest common subsequence problem
SLS'07 Proceedings of the 2007 international conference on Engineering stochastic local search algorithms: designing, implementing and analyzing effective heuristics
An enhanced beam search algorithm for the Shortest Common Supersequence Problem
Engineering Applications of Artificial Intelligence
A hyper-heuristic for the Longest Common Subsequence problem
Computational Biology and Chemistry
Computing longest common subsequences with the B-cell algorithm
ICARIS'12 Proceedings of the 11th international conference on Artificial Immune Systems
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The Longest Common Subsequence problem seeks a longest subsequence of every member of a given set of strings. It has applications, among others, in data compression, FPGA circuit minimization, and bioinformatics. The problem is NP-hard for more than two input strings, and the existing exact solutions are impractical for large input sizes. Therefore, several approximation and (meta) heuristic algorithms have been proposed which aim at finding good, but not necessarily optimal, solutions to the problem. In this paper, we propose a new algorithm based on the constructive beam search method. We have devised a novel heuristic, inspired by the probability theory, intended for domains where the input strings are assumed to be independent. Special data structures and dynamic programming methods are developed to reduce the time complexity of the algorithm. The proposed algorithm is compared with the state-of-the-art over several standard benchmarks including random and real biological sequences. Extensive experimental results show that the proposed algorithm outperforms the state-of-the-art by giving higher quality solutions with less computation time for most of the experimental cases.