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dc.contributor.author
Salto, Carolina
dc.contributor.author
Luna, Francisco
dc.contributor.author
Alba, Enrique
dc.date.available
2018-02-14T18:27:22Z
dc.date.issued
2014-10
dc.identifier.citation
Salto, Carolina; Luna, Francisco; Alba, Enrique; Enhancing distributed EAs by a proactive strategy; Springer; Cluster Computing-the Journal Of Networks Software Tools And Applications; 17; 2; 10-2014; 219-229
dc.identifier.issn
1386-7857
dc.identifier.uri
http://hdl.handle.net/11336/36446
dc.description.abstract
In this work we propose a new distributed evolutionary algorithm that uses a proactive strategy to adapt its migration policy and the mutation rate. The proactive decision is carried out locally in each subpopulation based on the entropy of that subpopulation. In that way, each subpopulation can change their own incoming flow of individuals by asking their neighbors for more frequent or less frequent migrations in order to maintain the genetic diversity at a desired level. Moreover, this proactive strategy is reinforced by adapting the mutation rate while the algorithm is searching for the problem solution. All these strategies avoid the subpopulations to get trapped into local minima. We conduct computational experiments on large instances of the NK landscape problem which have shown that our proactive approach outperforms traditional dEAs, particularly for not highly rugged landscapes, in which it does not only reaches the most accurate solutions, but it does the fastest.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Springer
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Proactive Behaviour
dc.subject
Distributed Eas
dc.subject
Migration Period
dc.subject.classification
Ciencias de la Computación
dc.subject.classification
Ciencias de la Computación e Información
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Enhancing distributed EAs by a proactive strategy
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2018-02-14T13:20:38Z
dc.journal.volume
17
dc.journal.number
2
dc.journal.pagination
219-229
dc.journal.pais
Alemania
dc.journal.ciudad
Berlin
dc.description.fil
Fil: Salto, Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Pampa; Argentina
dc.description.fil
Fil: Luna, Francisco. Universidad Carlos III de Madrid; España
dc.description.fil
Fil: Alba, Enrique. Universidad de Málaga; España
dc.journal.title
Cluster Computing-the Journal Of Networks Software Tools And Applications
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1007/s10586-013-0321-4
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs10586-013-0321-4
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