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dc.contributor.author
Pelikan, Martin
dc.contributor.author
Katzgraber, Helmut G.
dc.date.accessioned
2022-09-08T09:24:31Z
dc.date.available
2017-06-09T00:05:28Z
dc.date.available
2022-09-08T09:24:31Z
dc.date.issued
2009-07
dc.identifier.isbn
978-1-60558-325-9
en_US
dc.identifier.other
10.1145/1569901.1570017
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/20981
dc.description.abstract
This paper provides an in-depth empirical analysis of several hybrid evolutionary algorithms on the one-dimensional spin glass model with power-law interactions. The considered spin glass model provides a mechanism for tuning the effective range of interactions, what makes the problem interesting as an algorithm benchmark. As algorithms, the paper considers the genetic algorithm (GA) with twopoint and uniform crossover, and the hierarchical Bayesian optimization algorithm (hBOA). hBOA is shown to outperform both variants of GA, whereas GA with uniform crossover is shown to perform worst. The differences between the compared algorithms become more significant as the problem size grows and as the range of interactions decreases. Unlike for GA with uniform crossover, for hBOA and GA with twopoint crossover, instances with short-range interactions are shown to be easier. The paper also points out interesting avenues for future research.
en_US
dc.language.iso
en
en_US
dc.publisher
Association for Computing Machinery
en_US
dc.subject
Spin glass
en_US
dc.subject
power-law interactions
en_US
dc.subject
hierarchical BOA
en_US
dc.subject
genetic algorithm
en_US
dc.subject
estimation of distribution algorithms
en_US
dc.subject
evolutionary computation
en_US
dc.subject
hybridization
en_US
dc.title
Analysis of evolutionary algorithms on the one-dimensional spin glass with power-law interactions
en_US
dc.type
Conference Paper
dc.date.published
2009-07-08
ethz.book.title
Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation (GECCO '09)
en_US
ethz.pages.start
843
en_US
ethz.pages.end
850
en_US
ethz.event
11th Annual Conference on Genetic and Evolutionary Computation (GECCO 2009)
en_US
ethz.event.location
Montreal, Canada
en_US
ethz.event.date
July 8-12, 2009
en_US
ethz.publication.place
New York, NY
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2017-06-09T00:05:53Z
ethz.source
ECIT
ethz.identifier.importid
imp59364cc2de1be47828
ethz.ecitpid
pub:33596
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2017-07-12T14:48:53Z
ethz.rosetta.lastUpdated
2017-07-12T14:48:53Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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