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A genetic approach for long term virtual organization distribution

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A genetic approach for long term virtual organization distribution

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dc.contributor.author Sánchez Anguix, Víctor es_ES
dc.contributor.author Valero Cubas, Soledad es_ES
dc.contributor.author García Fornes, Ana María es_ES
dc.date.accessioned 2014-02-24T15:33:24Z
dc.date.issued 2011-04
dc.identifier.issn 0218-2130
dc.identifier.uri http://hdl.handle.net/10251/35920
dc.description Electronic versíon of an article published as International Journal on Artificial Intelligent Tools, Volume 20, issue 2, 2011. 10.1142/S0218213011000152. © World Scientific Publishing Company
dc.description.abstract [EN] An agent-based Virtual Organization is a complex entity where dynamic collections of agents agree to share resources in order to accomplish a global goal or offer a complex service. An important problem for the performance of the Virtual Organization is the distribution of the agents across the computational resources. The final distribution should provide a good load balancing for the organization. In this article, a genetic algorithm is applied to calculate a proper distribution across hosts in an agent-based Virtual Organization. Additionally, an abstract multi-agent system architecture which provides infrastructure for Virtual Organization distribution is introduced. The developed genetic solution employs an elitist crossover operator where one of the children inherits the most promising genetic material from the parents with higher probability. In order to validate the genetic proposal, the designed genetic algorithm has been successfully compared to several heuristics in different scenarios. © 2011 World Scientific Publishing Company. es_ES
dc.description.sponsorship This work is supported by TIN2008-04446, TIN2009-13839-C03-01, CSD2007-00022 and FPU grant AP2008-00600 of the Spanish government, and PROMETEO 2008/051 of the Generalitat Valenciana.
dc.format.extent 25 es_ES
dc.language Inglés es_ES
dc.publisher World Scientific Publishing es_ES
dc.relation.ispartof International Journal on Artificial Intelligence Tools es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Genetic algorithms es_ES
dc.subject Multi-agent systems es_ES
dc.subject Virtual organizations es_ES
dc.subject Agent based es_ES
dc.subject Complex entities es_ES
dc.subject Complex services es_ES
dc.subject Computational resources es_ES
dc.subject Crossover operator es_ES
dc.subject Genetic approach es_ES
dc.subject Genetic materials es_ES
dc.subject Load-Balancing es_ES
dc.subject Long term es_ES
dc.subject Multi-agent system architecture es_ES
dc.subject Virtual organization es_ES
dc.subject Computation theory es_ES
dc.subject Mathematical operators es_ES
dc.subject Multi agent systems es_ES
dc.subject Probabilistic logics es_ES
dc.subject Intelligent agents es_ES
dc.subject.classification CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title A genetic approach for long term virtual organization distribution es_ES
dc.type Artículo es_ES
dc.embargo.lift 10000-01-01
dc.embargo.terms forever es_ES
dc.identifier.doi 10.1142/S0218213011000152
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TIN2008-04446/ES/UNA PLATAFORMA PARA SISTEMAS MULTIAGENTE ABIERTOS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/Generalitat Valenciana//PROMETEO08%2F2008%2F051/ES/Advances on Agreement Technologies for Computational Entities (atforce)/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TIN2009-13839-C03-01/ES/Organizaciones Virtuales Adaptativas: Arquitecturas Y Metodos De Desarrollo/
dc.relation.projectID info:eu-repo/grantAgreement/MEC//CSD2007-00022/ES/Agreement Technologies/
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//AP2008-00600/ES/AP2008-00600/
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Sánchez Anguix, V.; Valero Cubas, S.; García Fornes, AM. (2011). A genetic approach for long term virtual organization distribution. International Journal on Artificial Intelligence Tools. 20(2):271-295. https://doi.org/10.1142/S0218213011000152 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename 23rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems es_ES
dc.relation.conferencedate June 01-04, 2010 es_ES
dc.relation.conferenceplace Cordoba, Spain es_ES
dc.relation.publisherversion http://dx.doi.org/10.1142/S0218213011000152 es_ES
dc.description.upvformatpinicio 271 es_ES
dc.description.upvformatpfin 295 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 20 es_ES
dc.description.issue 2 es_ES
dc.relation.senia 41478
dc.contributor.funder Ministerio de Ciencia e Innovación
dc.contributor.funder Generalitat Valenciana
dc.contributor.funder Ministerio de Educación y Ciencia es_ES


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