Multipopulation-based multi-level parallel enhanced Jaya algorithms
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http://hdl.handle.net/10045/91222
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Campo DC | Valor | Idioma |
---|---|---|
dc.contributor | UniCAD: Grupo de investigación en CAD/CAM/CAE de la Universidad de Alicante | es_ES |
dc.contributor.author | Migallón Gomis, Héctor | - |
dc.contributor.author | Jimeno-Morenilla, Antonio | - |
dc.contributor.author | Sanchez-Romero, Jose-Luis | - |
dc.contributor.author | Rico, Héctor | - |
dc.contributor.author | Rao, Ravipudi Venkata | - |
dc.contributor.other | Universidad de Alicante. Departamento de Tecnología Informática y Computación | es_ES |
dc.date.accessioned | 2019-04-15T10:04:49Z | - |
dc.date.available | 2019-04-15T10:04:49Z | - |
dc.date.issued | 2019-03 | - |
dc.identifier.citation | The Journal of Supercomputing. 2019, 75(3): 1697-1716. doi:10.1007/s11227-019-02759-z | es_ES |
dc.identifier.issn | 0920-8542 (Print) | - |
dc.identifier.issn | 1573-0484 (Online) | - |
dc.identifier.uri | http://hdl.handle.net/10045/91222 | - |
dc.description.abstract | To solve optimization problems, in the field of engineering optimization, an optimal value of a specific function must be found, in a limited time, within a constrained or unconstrained domain. Metaheuristic methods are useful for a wide range of scientific and engineering applications, which accelerate being able to achieve optimal or near-optimal solutions. The metaheuristic method called Jaya has generated growing interest because of its simplicity and efficiency. We present Jaya-based parallel algorithms to efficiently exploit cluster computing platforms (heterogeneous memory platforms). We propose a multi-level parallel algorithm, in which, to exploit distributed-memory architectures (or multiprocessors), the outermost layer of the Jaya algorithm is parallelized. Moreover, in internal layers, we exploit shared-memory architectures (or multicores) by adding two more levels of parallelization. This two-level internal parallel algorithm is based on both a multipopulation structure and an improved heuristic search path relative to the search path of the sequential algorithm. The multi-level parallel algorithm obtains average efficiency values of 84% using up to 120 and 135 processes, and slightly accelerates the convergence with respect to the sequential Jaya algorithm. | es_ES |
dc.description.sponsorship | This research was supported by the Spanish Ministry of Economy and Competitiveness under Grant TIN2015-66972-C5-4-R and Grant TIN2017-89266-R, co-financed by FEDER funds (MINECO/FEDER/UE). | es_ES |
dc.language | eng | es_ES |
dc.publisher | Springer US | es_ES |
dc.rights | © Springer Science+Business Media, LLC, part of Springer Nature 2019 | es_ES |
dc.subject | Jaya | es_ES |
dc.subject | Optimization | es_ES |
dc.subject | Metaheuristic | es_ES |
dc.subject | Multipopulation | es_ES |
dc.subject | Parallelism | es_ES |
dc.subject | MPI/OpenMP | es_ES |
dc.subject.other | Arquitectura y Tecnología de Computadores | es_ES |
dc.title | Multipopulation-based multi-level parallel enhanced Jaya algorithms | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.peerreviewed | si | es_ES |
dc.identifier.doi | 10.1007/s11227-019-02759-z | - |
dc.relation.publisherversion | https://doi.org/10.1007/s11227-019-02759-z | es_ES |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//TIN2015-66972-C5-4-R | - |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-89266-R | - |
Aparece en las colecciones: | INV - UNICAD - Artículos de Revistas |
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2019_Migallon_etal_JSupercomputing_final.pdf | Versión final (acceso restringido) | 1,1 MB | Adobe PDF | Abrir Solicitar una copia |
2019_Migallon_etal_JSupercomputing_preprint.pdf | Preprint (acceso abierto) | 397,92 kB | Adobe PDF | Abrir Vista previa |
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