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Adaptive and Multilevel Metaheuristics

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Handbook of Heuristics

Abstract

For the last decades, metaheuristics have become ever more popular as a tool to solve a large class of difficult optimization problems. However, determining the best configuration of a metaheuristic, which includes the program flow and the parameter settings, remains a difficult task. Adaptive metaheuristics (that change their configuration during the search) and multilevel metaheuristics (that change their configuration during the search by means of a metaheuristic) can be a solution for this. This chapter intends to make a quick review of the latest trends in adaptive metaheuristics and in multilevel metaheuristics.

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Author information

Authors and Affiliations

  1. Université de Bretagne-Sud, Lab-STICC, CNRS, Lorient, France

    Marc Sevaux

  2. University of Antwerp, Antwerp, Belgium

    Kenneth Sörensen

  3. School of Mathematics, Statistics, and Computer Science, University of KwaZulu-Natal, Durban, South Africa

    Nelishia Pillay

Authors
  1. Marc Sevaux
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  2. Kenneth Sörensen
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  3. Nelishia Pillay
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Corresponding author

Correspondence to Marc Sevaux .

Editor information

Editors and Affiliations

  1. Department of Statistics and Operations, University of Valencia, Valencia, Spain

    Rafael Martí

  2. University of Florida Industrial and Systems Engineering, Gainesville, Florida, USA

    Pardalos Panos

  3. Modeling and Optimization Group, Amazon (United States) , Seattle, Washington, USA

    Mauricio G. C. Resende

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Sevaux, M., Sörensen, K., Pillay, N. (2018). Adaptive and Multilevel Metaheuristics. In: Martí, R., Panos, P., Resende, M. (eds) Handbook of Heuristics. Springer, Cham. https://doi.org/10.1007/978-3-319-07153-4_16-1

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  • DOI: https://doi.org/10.1007/978-3-319-07153-4_16-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07153-4

  • Online ISBN: 978-3-319-07153-4

  • eBook Packages: Springer Reference MathematicsReference Module Computer Science and Engineering

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