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2018 | OriginalPaper | Buchkapitel

20. Memetic Algorithms

verfasst von: Carlos Cotta, Luke Mathieson, Pablo Moscato

Erschienen in: Handbook of Heuristics

Verlag: 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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Metadaten
Titel
Memetic Algorithms
verfasst von
Carlos Cotta
Luke Mathieson
Pablo Moscato
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-07124-4_29

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