Abstract
Finding the common part of a set of strings has many important applications, for example, in pattern recognition or computational biology. In computer science, this problem is known as the longest common subsequence problem. In this work we present a probabilistic beam search approach to solve this classical problem. To our knowledge, this algorithm is the first stochastic local search algorithm proposed for this problem. The results show the great potential of our algorithm when compared to existing heuristic methods.
This work was supported by grant TIN-2005-08818-C04-01 (OPLINK) of the Spanish government, and by the Ramón y Cajal program of the Spanish Ministry of Science and Technology of which Christian Blum is a research fellow.
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Blum, C., Blesa, M.J. (2007). Probabilistic Beam Search for the Longest Common Subsequence Problem. In: Stützle, T., Birattari, M., H. Hoos, H. (eds) Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics. SLS 2007. Lecture Notes in Computer Science, vol 4638. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74446-7_11
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DOI: https://doi.org/10.1007/978-3-540-74446-7_11
Publisher Name: Springer, Berlin, Heidelberg
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