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Inspired by NatureCombining Local and Global Search: A Multi-objective Evolutionary Algorithm for Cartesian Genetic Programming

Inspired by Nature: Combining Local and Global Search: A Multi-objective Evolutionary Algorithm... [This work investigates the effects of the periodization of local and global multi-objective search algorithms. We rely on a model for periodization and define a multi-objective evolutionary algorithm adopting concepts from Evolutionary Strategies and NSGAII. We show that our method excels for the evolution of digital circuits on the Cartesian Genetic Programming model as well as on some standard benchmarks such as the ZDT6, especially when periodized with standard multi-objective genetic algorithms.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Inspired by NatureCombining Local and Global Search: A Multi-objective Evolutionary Algorithm for Cartesian Genetic Programming

Part of the Emergence, Complexity and Computation Book Series (volume 28)
Editors: Stepney, Susan; Adamatzky, Andrew
Kaufmann, Paul; Platzner, Marco
Inspired by Nature — Oct 27, 2017
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Publisher
Springer International Publishing
Copyright
© Springer International Publishing AG 2018
ISBN
978-3-319-67996-9
Pages
175 –194
DOI
10.1007/978-3-319-67997-6_8
Publisher site
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Abstract

[This work investigates the effects of the periodization of local and global multi-objective search algorithms. We rely on a model for periodization and define a multi-objective evolutionary algorithm adopting concepts from Evolutionary Strategies and NSGAII. We show that our method excels for the evolution of digital circuits on the Cartesian Genetic Programming model as well as on some standard benchmarks such as the ZDT6, especially when periodized with standard multi-objective genetic algorithms.]

Published: Oct 27, 2017

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