Abstract
In this paper we propose a Beam-ACO approach for a combinatorial optimization problem known as the repetition-free longest common subsequence problem. Given two input sequences \(x\) and \(y\) over a finite alphabet \(\varSigma \), this problem concerns to find a longest common subsequence of \(x\) and \(y\) in which no letter is repeated. Beam-ACO algorithms are combinations between the metaheuristic ant colony optimization and a deterministic tree search technique called beam search. The algorithm that we present is an adaptation of a previously published Beam-ACO algorithm for the classical longest common subsequence problem. The results of the proposed algorithm outperform existing heuristics from the literature.
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Acknowledgments
This work was supported by grants TIN2012-37930, TIN2010-14931 and TIN2007-66523 of the Spanish Government, and project 2009-SGR1137 of the Generalitat de Catalunya. In addition, support is acknowledged from IKERBASQUE (Basque Foundation for Science) and the Basque Saiotek and Research Groups 2013-2018 (IT-609-13) programs.
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Blum, C., Blesa, M.J., Calvo, B. (2014). Beam-ACO for the Repetition-Free Longest Common Subsequence Problem. In: Legrand, P., Corsini, MM., Hao, JK., Monmarché, N., Lutton, E., Schoenauer, M. (eds) Artificial Evolution. EA 2013. Lecture Notes in Computer Science(), vol 8752. Springer, Cham. https://doi.org/10.1007/978-3-319-11683-9_7
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DOI: https://doi.org/10.1007/978-3-319-11683-9_7
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