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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 S, 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.
CitationBlum, C.; Blesa, M.; Calvo, B. Beam-ACO for the repetition-free longest common subsequence problem. A: Biennal International Conference on Artificial Evolution. "Artificial Evolution 2013 (Evolution Artificielle 2013): 11th Biennal International Conference on Artificial Evolution: proceedings: 21-23 October 2013, Bordeaux, France". Bordeaux: 2013, p. 187-198.
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