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A novel hybrid evolutionary strategy and its periodization with multi-objective genetic optimizers

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3 Author(s)
Kaufmann, P. ; Dept. of Comput. Sci., Univ. of Paderborn, Paderborn, Germany ; Knieper, T. ; Platzner, M.

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

Published in:
Evolutionary Computation (CEC), 2010 IEEE Congress on

Date of Conference: 18-23 July 2010

Page(s):
1 - 8
Print ISBN:
978-1-4244-6909-3
INSPEC Accession Number:
11567920
Conference Location :
Barcelona
Digital Object Identifier :
10.1109/CEC.2010.5586541
Product Type:
Conference Publications

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