dc.creatorBilbao, Martín
dc.creatorLeguizamón, Guillermo
dc.date2019-10
dc.date2019
dc.date2020-03-16T16:40:14Z
dc.date.accessioned2023-07-14T18:59:05Z
dc.date.available2023-07-14T18:59:05Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/90896
dc.identifierisbn:978-987-688-377-1
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7433540
dc.descriptionIn this paper, we study a parallelization of CHC algorithm (Crossover elitism population, Half uniform crossover combination, Cataclysm mutation) to solve the problem of placement of wind turbines in a wind farm. We also analyze the solutions obtained when we use both, the sequential and parallel version for the CHC algorithm. In this case we study the behavior of parallel metaheuristics using an island model to distribute the algorithm in different cores and compare this proposal with the sequential version to analyse the number of evaluation to find the best configuration, output power extracted, plant coefficient, evaluations needed, memory consumption, and execution time for different number of core and different problem sizes.
dc.descriptionXX Workshop Agentes y Sistemas Inteligentes.
dc.descriptionRed de Universidades con Carreras en Informática
dc.formatapplication/pdf
dc.format85-94
dc.languagees
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.subjectCiencias Informáticas
dc.subjectWind Energy
dc.subjectWeibull Distribution
dc.subjectWind Power
dc.subjectEvolutionary Computation
dc.subjectMetaheuristics
dc.titleMulticore Parallelization of CHC for Optimal Aerogenerator Placement in Wind Farms
dc.typeObjeto de conferencia
dc.typeObjeto de conferencia


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