Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7546
Title: Effect of spatial locality on an evolutionary algorithm for multimodal optimization
Authors: Wong, Ka-Chun 
Prof. LEUNG Kwong Sak 
Wong, Man-Hon 
Issue Date: 2010
Publisher: Springer Verlag
Source: 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
Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 
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.
Type: Conference Paper
URI: http://hdl.handle.net/20.500.11861/7546
ISBN: 3642122388
978-364212238-5
ISSN: 03029743
DOI: 10.1007/978-3-642-12239-2_50
Appears in Collections:Applied Data Science - Publication

Show full item record

SCOPUSTM   
Citations

20
checked on Nov 3, 2024

Page view(s)

32
Last Week
1
Last month
checked on Nov 13, 2024

Google ScholarTM

Impact Indices

Altmetric

PlumX

Metrics


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.