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An analysis of the operation of differential evolution at high and low crossover rates
List of Titles
An analysis of the operation of differential evolution at high and low crossover rates
Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/80955
- Title
- An analysis of the operation of differential evolution at high and low crossover rates
- Author(s)
- Montgomery, James; Chen, Stephen
- Abstract
- A key parameter affecting the operation of differential evolution (DE) is the crossover rate Cr 2 [0; 1]. While very low values are recommended for and used with separable problems, on non-separable problems, which include most realworld problems, Cr = 0:9 has become the de facto standard, working well across a large range of problem domains. Recent work on separable and non-separable problems has shown that lower-dimensional searches can play an important role in the performance of search techniques in higher-dimensional search spaces. However, the standard value of Cr = 0:9 implies a very high-dimensional search, which is not effective for other search techniques. An analysis of Cr across its range [0; 1] provides insight into how its value affects the performance of DE and suggests how low values may be used to improve the performance of DE. This new understanding of the operation of DE at high and low crossover rates is useful for analysing how adaptive parameters affect DE performance and leads to new suggestions for how adaptive DE techniques might be developed.
- Publication type
- Conference paper
- Research centre
- Swinburne University of Technology. Faculty of Information and Communication Technologies
- Source
- Proceedings of the 2010 IEEE Congress on Evolutionary Computation (CEC 2010), held as part of the 2010 IEEE World Congress on Computational Intelligence (IEEE WCCI 2010), Barcelona, Spain, 18-23 July 2010, pp. 881-888
- Publication year
- 2010
- FOR Code(s)
- 010303 Optimisation; 080108 Neural, Evolutionary and Fuzzy Computation
- Keyword(s)
- Crossover rate; Differential evolution
- Publisher
- IEEE
- ISBN
- 9781424481262
- Publisher URL
- http://dx.doi.org/10.1109/CEC.2010.5586128
- Copyright
- Copyright © 2010 IEEE. Published version of the paper reproduced here in accordance with the copyright policy of the publisher. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
- Full text

- Peer reviewed


