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Effect of spatial locality on an evolutionary algorithm for multimodal optimization
Author(s)
Date Issued
2010
Publisher
Springer Verlag
Conference
ISBN
3642122388
978-364212238-5
ISSN
03029743
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6024 LNCS, Issue PART 1, pp. 481 - 490
Type
Conference Paper
Abstract
To explore the effect of spatial locality, crowding differential evolution is incorporated with spatial locality for multimodal optimization. Instead of random trial vector generations, it takes advantages of spatial locality to generate fitter trial vectors. Experiments were conducted to compare the proposed algorithm (CrowdingDE-L) with the state-of-the-art algorithms. Further experiments were also conducted on a real world problem. The experimental results indicate that CrowdingDE-L has a competitive edge over the other algorithms tested. © 2010 Springer-Verlag Berlin Heidelberg.
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