Beam-ACO for the Repetition-Free Longest Common Subsequence Problem
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.
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.
- 3.Blum, C.: Beam-ACO for the longest common subsequence problem. In: Fogel, G., et al. (eds.) Proceedings of CEC 2010 - Congress on Evolutionary Computation, vol. 2. IEEE Press, Piscataway (2010)Google Scholar
- 13.Storer, J.: Data Compression: Methods and Theory. Computer Science Press, Rockville (1988)Google Scholar