Hybrid Metaheuristics

  • Christian Blum
  • Jakob Puchinger
  • Günther Raidl
  • Andrea Roli
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 45)

Abstract

One of the most interesting recent trends for what concerns research on metaheuristics is their hybridization with other techniques for optimization. In fact, the focus of research on metaheuristics has notably shifted from an algorithm-oriented point of view to a problem-oriented point of view. In other words, in contrast to promoting a certain metaheuristic, as, for example, in the eighties and the first half of the nineties, nowadays researchers focus much more on solving, as best as possible, the problem at hand. This has inevitably led to research that aims at combining different algorithmic components for the design of algorithms that are more powerful than the ones resulting from the implementation of pure metaheuristic strategies. Interestingly, the trend of hybridization is not restricted to the combination of algorithmic components originating from different metaheuristics, but has also been extended to the combination of exact algorithms and metaheuristics. In this chapter, we provide an overview of the most important lines of hybridization. In addition to representative examples, we present a literature review for each of the considered hybridization types.

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Copyright information

© Springer Science+Business Media LLC 2011

Authors and Affiliations

  • Christian Blum
    • 1
  • Jakob Puchinger
  • Günther Raidl
  • Andrea Roli
  1. 1.ALBCOM Research GroupUniversitat Politècnica de CatalunyaBarcelonaSpain

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