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A Multilevel Probabilistic Beam Search Algorithm for the Shortest Common Supersequence Problem

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  • José E Gallardo

Abstract

The shortest common supersequence problem is a classical problem with many applications in different fields such as planning, Artificial Intelligence and especially in Bioinformatics. Due to its NP-hardness, we can not expect to efficiently solve this problem using conventional exact techniques. This paper presents a heuristic to tackle this problem based on the use at different levels of a probabilistic variant of a classical heuristic known as Beam Search. The proposed algorithm is empirically analysed and compared to current approaches in the literature. Experiments show that it provides better quality solutions in a reasonable time for medium and large instances of the problem. For very large instances, our heuristic also provides better solutions, but required execution times may increase considerably.

Suggested Citation

  • José E Gallardo, 2012. "A Multilevel Probabilistic Beam Search Algorithm for the Shortest Common Supersequence Problem," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-14, December.
    • Handle: RePEc:plo:pone00:0052427
    DOI: 10.1371/journal.pone.0052427
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