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Article
Greedy Population Sizing for Evolutionary Algorithms
Proceedings of the 2007 IEEE Congress on Evolutionary Computation (2007: Sep. 25-28, Singapore)
  • Ekaterina Smorodkina
  • Daniel R. Tauritz, Missouri University of Science and Technology
Abstract

The number of parameters that need to be man ually tuned to achieve good performance of Evolutionary Algorithms and the dependency of the parameters on each other make this potentially robust and efficient computational method very time consuming and difficult to use. This paper introduces a Greedy Population Sizing method for Evolutionary Algo rithms (GPS-EA), an automated population size tuning method that does not require any population size related parameters to be specified or manually tuned a priori. Theoretical analysis of the number of function evaluations needed by the GPS EA to produce good solutions is provided. We also perform an empirical comparison of the performance of the GPS-EA to the performance of an EA with a manually tuned fixed population size. Both theoretical and empirical results show that using GPS-EA eliminates the need for manually tuning the population size parameter, while finding good solutions. This comes at the price of using twice as many function evaluations as needed by the EA with an optimal fixed population size; this, in practice, is a low price considering the amount of time and effort it takes to find this optimal population size manually.

Meeting Name
2007 IEEE Congress on Evolutionary Computation (2007: Sep. 25-28, Singapore)
Department(s)
Computer Science
Keywords and Phrases
  • Evolutionary Algorithms,
  • Greedy Population Sizing,
  • Automated Population Size Tuning Method
International Standard Book Number (ISBN)
978-1-4244-1339-3
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2007 Intitute of Electrical and Electronics Engineers, Inc., All rights reserved.
Publication Date
1-1-2007
Disciplines
Citation Information
Ekaterina Smorodkina and Daniel R. Tauritz. "Greedy Population Sizing for Evolutionary Algorithms" Proceedings of the 2007 IEEE Congress on Evolutionary Computation (2007: Sep. 25-28, Singapore) (2007) p. 2181 - 2187 ISSN: 1089-778X
Available at: http://works.bepress.com/daniel-tauritz/40/