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A Probabilistic Beam Search Approach to the Shortest Common Supersequence Problem.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Rangan, C. Pandu
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Hemert, Jano
Blum, Christian
Cotta, Carlos
Fernández, Antonio J.
Gallardo, José E.
Source :
Evolutionary Computation in Combinatorial Optimization (9783540716143); 2007, p36-47, 12p
Publication Year :
2007

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540716143
Database :
Supplemental Index
Journal :
Evolutionary Computation in Combinatorial Optimization (9783540716143)
Publication Type :
Book
Accession number :
32943210
Full Text :
https://doi.org/10.1007/978-3-540-71615-0_4