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 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.

• Type: Conference
• Year: 2007
• Where: EVOW
• Authors: Christian Blum, Carlos Cotta, Antonio J. Fernández, José E. Gallardo
• Keywords: Artificial Intelligence, Beam Search, EVOW 2007, Greedy Constructive Heuristics, Probabilistic Beam Search