A probabilistic beam search approach to the shortest common supersequence problem

Authors:
Christian Blum;Carlos Cotta;Antonio J. Fernández;José E. Gallardo
Affiliations:
ALBCOM, Dept. Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya, Barcelona, Spain;Dept. Lenguajes y Ciencias de la Computación, ETSI Informática, Universidad de Málaga, Málaga, Spain;Dept. Lenguajes y Ciencias de la Computación, ETSI Informática, Universidad de Málaga, Málaga, Spain;Dept. Lenguajes y Ciencias de la Computación, ETSI Informática, Universidad de Málaga, Málaga, Spain
Venue:
EvoCOP'07 Proceedings of the 7th European conference on Evolutionary computation in combinatorial optimization
Year:
2007

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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.