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A Probabilistic Beam Search Approach to the Shortest Common Supersequence Problem

The Shortest Common Supersequence Problem (SCSP) is a well-known hard combinatorial optimization problem that formalizes many real world problems. This paper presents a novel randomized search strategy, called probabilistic beam search (PBS), based on the hybridization between beam search and greedy...

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Detalles Bibliográficos
Autores principales: Blum, Christian, Cotta, Carlos, Fernández, Antonio J., Gallardo, José E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120107/
http://dx.doi.org/10.1007/978-3-540-71615-0_4
Descripción
Sumario:The Shortest Common Supersequence Problem (SCSP) is a well-known hard combinatorial optimization problem that formalizes many real world problems. This paper presents a novel randomized search strategy, called probabilistic beam search (PBS), based on the hybridization between beam search and greedy constructive heuristics. PBS is competitive (and sometimes better than) previous state-of-the-art algorithms for solving the SCSP. The paper describes PBS and provides an experimental analysis (including comparisons with previous approaches) that demonstrate its usefulness.