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A probabilistic beam search approach to the shortest common supersequence problem
dc.contributor.author | Blum, Christian |
dc.contributor.author | Cotta, C. |
dc.contributor.author | Fernández, Antonio J. |
dc.contributor.author | Gallardo, Francisco |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics |
dc.date.accessioned | 2016-05-27T08:25:00Z |
dc.date.available | 2016-05-27T08:25:00Z |
dc.date.issued | 2006-11 |
dc.identifier.citation | Blum, C., Cotta, C., Fernández, A., Gallardo, F. "A probabilistic beam search approach to the shortest common supersequence problem". 2006. |
dc.identifier.uri | http://hdl.handle.net/2117/87415 |
dc.description.abstract | 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. |
dc.format.extent | 12 p. |
dc.language.iso | eng |
dc.relation.ispartofseries | LSI-06-36-R |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica |
dc.subject.other | Combinatorial mathematics |
dc.subject.other | Greedy algorithms |
dc.subject.other | Optimisation |
dc.subject.other | Probability |
dc.subject.other | Search problems |
dc.subject.other | String matching |
dc.title | A probabilistic beam search approach to the shortest common supersequence problem |
dc.type | External research report |
dc.rights.access | Open Access |
local.identifier.drac | 18538477 |
dc.description.version | Postprint (published version) |
local.citation.author | Blum, C.; Cotta, C.; Fernández, A.; Gallardo, F. |
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