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Hybridizations of Metaheuristics With Branch & Bound Derivates

  • Christian Blum
  • Carlos Cotta
  • Antonio J. Fernández
  • José E. Gallardo
  • Monaldo Mastrolilli
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 114)

An important branch of hybrid metaheuristics concerns the hybridization with branch & bound derivatives. In this chapter we present examples for two different types of hybridization. The first one concerns the use of branch & bound features within construction-based metaheuristics in order to increase their efficiancy. The second example deals with the use of a metaheuristic, in our case a memetic algorithm, in order to increase the efficiancy of branch & bound, respectively branch & bound derivatives such as beam search. The quality of the resulting hybrid techniques is demonstrated by means of the application to classical string problems: the longest common subsequence problem and the shortest common supersequence problem.

Keywords

Search Tree Target Node Memetic Algorithm Greedy Randomize Adaptive Search Procedure Beam Search 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Christian Blum
    • 1
  • Carlos Cotta
  • Antonio J. Fernández
  • José E. Gallardo
  • Monaldo Mastrolilli
  1. 1.Dept. Llenguatges i Sistemes InformáticsUniversitat Politècnica de CatalunyaSpain

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