dc.creatorGonzalez, Paulo
dc.creatorIglesias, Philip
dc.creatorSilva, Estefanía
dc.date2024-01-16T17:39:32Z
dc.date2024-01-16T17:39:32Z
dc.date2023
dc.date.accessioned2024-05-02T20:32:03Z
dc.date.available2024-05-02T20:32:03Z
dc.identifierhttp://repositorio.ucm.cl/handle/ucm/5178
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9275363
dc.descriptionThis work presents a modified version of the Particle Swarm Optimization (PSO) based on improved parameters, Opposite-Based-Learning parametrization, and constraints based on forbidden locations in the search space. The method exhibits fast convergence and stability in the search for optimal parameter values. It has been tested on classical test functions proposed in the literature and compared with the performance of the seminal method and a recently proposed one. Representative results demonstrate the method’s potential to be applied in realistic situations.
dc.languageen
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
dc.sourceProceedings - International Conference of the Chilean Computer Science Society, SCCC, 2023, 1-5
dc.subjectComputer science
dc.subjectMetaheuristics
dc.subjectParticle swarm optimization
dc.subjectConvergence
dc.titleRestricted particle swarm optimization meta-heuristic method
dc.typeArticle


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