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Metaheuristic Hybrids

  • Günther R. Raidl
  • Jakob Puchinger
  • Christian Blum
Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 272)

Abstract

Over the last decades, so-called hybrid optimization approaches have become increasingly popular for addressing hard optimization problems. In fact, when looking at leading applications of metaheuristics for complex real-world scenarios, many if not most of them do not purely adhere to one specific classical metaheuristic model but rather combine different algorithmic techniques. Concepts from different metaheuristics are often hybridized with each other, but they are also often combined with other optimization techniques such as tree-search, dynamic programming and methods from the mathematical programming, constraint programming, and SAT-solving fields. Such combinations aim at exploiting the particular advantages of the individual components, and in fact well-designed hybrids often perform substantially better than their “pure” counterparts. Many very different ways of hybridizing metaheuristics are described in the literature, and unfortunately it is usually difficult to decide which approach(es) are most appropriate in a particular situation. This chapter gives an overview on this topic by starting with a classification of metaheuristic hybrids and then discussing several prominent design templates which are illustrated by concrete examples.

Notes

Acknowledgements

Günther R. Raidl is supported by the Austrian Science Fund (FWF) under grants P27615 and W1260.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Günther R. Raidl
    • 1
  • Jakob Puchinger
    • 2
    • 3
  • Christian Blum
    • 4
  1. 1.Institute of Logic and ComputationViennaAustria
  2. 2.Laboratoire Genie Industriel, CentraleSupélecUniversité Paris-SaclayGif-sur-YvetteFrance
  3. 3.Institut de Recherche Technologique SystemXPalaiseauFrance
  4. 4.Artificial Intelligence Research Institute (IIIA-CSIC)BellaterraSpain

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