A hyper-heuristic approach to automated generation of mutation operators for evolutionary programming

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A hyper-heuristic approach to automated generation of mutation operators for evolutionary programming

Evolutionary programming can solve black-box function optimisation problems by evolving a population of numerical vectors. The variation component in the evolutionary process is supplied by a mutation operator, which is typically a Gaussian, Cauchy, or Lévy probability distribution. In this paper, w...

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Bibliographic Details
Main Authors:	Hong, Libin, Drake, John H., Woodward, John R., Özcan, Ender
Format:	Article
Published:	Elsevier 2017
Subjects:	Evolutionary Programming; Genetic Programming; Automatic Design; Hyper-heuristics; Continuous Optimization
Online Access:	https://eprints.nottingham.ac.uk/47294/

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