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Adaptive and Multilevel Metaheuristics Read chapter Read first chapter

2018 | OriginalPaper | Chapter

20. Memetic Algorithms

Authors: Carlos Cotta, Luke Mathieson, Pablo Moscato

Published in: Handbook of Heuristics

Publisher: Springer International Publishing

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Abstract

Memetic algorithms provide one of the most effective and flexible metaheuristic approaches for tackling hard optimization problems. Memetic algorithms address the difficulty of developing high-performance universal heuristics by encouraging the exploitation of multiple heuristics acting in concert, making use of all available sources of information for a problem. This approach has resulted in a rich arsenal of heuristic algorithms and metaheuristic frameworks for many problems. This chapter discusses the philosophy of the memetic paradigm, lays out the structure of a memetic algorithm, develops several example algorithms, surveys recent work in the field, and discusses the possible future directions of memetic algorithms.
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Metadata
Title
Memetic Algorithms
Authors
Carlos Cotta
Luke Mathieson
Pablo Moscato
Copyright Year
2018
Book
Handbook of Heuristics

Print ISBN: 978-3-319-07123-7

Electronic ISBN: 978-3-319-07124-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-07124-4_29

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