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Alternative implementations of the Griewangk function

Published: 25 June 2005 Publication History

Abstract

The well-known Griewangk function, used for evaluation of evolutionary algorithms, becomes easier as the number of dimensions grows. This paper suggests three alternative implementations that maintain function complexity for high-dimensional versions of the problem. Diagonal slices of the search landscape and local search are used to demonstrate and evaluate the difficulty of each function.

References

[1]
D. Whitley, S. B. Rana, J. Dzubera, and K. E. Mathias. Evaluating evolutionary algorithms. Artificial Intelligence, 85(1-2):245--276, 1996.
[2]
Whitley D., M. Lunacek, J. Knight. "Ruffled by Ridges: How Evolutionary Algorithms Can Fail". In K. Deb, ed., GECCO (2) 2004: 294--306. Springer-Verlag.

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cover image ACM Conferences
GECCO '05: Proceedings of the 7th annual conference on Genetic and evolutionary computation
June 2005
2272 pages
ISBN:1595930108
DOI:10.1145/1068009
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 25 June 2005

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  1. evolutionary computation benchmarks
  2. test functions

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