Mostrando 8 resultados de: 8
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(3)
2016 IEEE Congress on Evolutionary Computation, CEC 2016(2)
2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings(1)
GECCO 2015 - Proceedings of the 2015 Genetic and Evolutionary Computation Conference(1)
GECCO 2016 - Proceedings of the 2016 Genetic and Evolutionary Computation Conference(1)
Área temáticas
Ciencias de la computación(5)
Programación informática, programas, datos, seguridad(3)
Matemáticas(2)
Métodos informáticos especiales(2)
Análisis(1)
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ODS 9: Industria, innovación e infraestructura(8)
ODS 17: Alianzas para lograr los objetivos(7)
ODS 7: Energía asequible y no contaminante(1)
Origen
scopus(8)
A refinement mechanism to improve particle swarm optimization
Conference ObjectAbstract: Due to its simplicity and effectiveness in solving many optimization problems, Particle Swarm OptimiPalabras claves:Hybrid algorithms, Local search mechanism, Particle Swarm OptimizationAutores:Hernán E. Aguirre, Tan W.R., Tanaka K., Zapotecas-Martínez S.Fuentes:scopusAnalysis and comparison of multi-objective evolutionary approaches on the multi-objective 1/0 unit commitment problem
Conference ObjectAbstract: In this paper, we analyze the behavior and compare the performance of three state-of-the-art Multi-oPalabras claves:Autores:Hernán E. Aguirre, Jacquin S., Tanaka K., Zapotecas-Martínez S.Fuentes:scopusApproaches for many-objective optimization: Analysis and comparison on MNK-landscapes
Conference ObjectAbstract: This work analyses the behavior and compares the performance of MOEA/D, IBEA using the binary additiPalabras claves:Autores:Hernán E. Aguirre, Liefooghe A., Tanaka K., Verel S., Zapotecas-Martínez S.Fuentes:scopusGeometric differential evolution in MOEA/D: A preliminary study
Conference ObjectAbstract: The multi-objective evolutionary algorithm based on decomposition (MOEA/D) is an aggregation-based aPalabras claves:Autores:Derbel B., Hernán E. Aguirre, Liefooghe A., Tanaka K., Zapotecas-Martínez S.Fuentes:scopusGeometric particle swarm optimization for multi-objective optimization using decomposition
Conference ObjectAbstract: Multi-objective evolutionary algorithms (MOEAs) based on decomposition are aggregation-based algoritPalabras claves:Decomposition-based moeas, Multi-objective combinatorial optimization, Particle Swarm OptimizationAutores:Hernán E. Aguirre, Moraglio A., Tanaka K., Zapotecas-Martínez S.Fuentes:scopusInjecting CMA-ES into MOEA/D
Conference ObjectAbstract: MOEA/D is an aggregation-based evolutionary algorithm which has been proved extremely efficient andPalabras claves:Covariance matrix adaption evolution strategy, Decomposition-based moeas, multi-objective optimizationAutores:Brockhoff D., Derbel B., Hernán E. Aguirre, Liefooghe A., Tanaka K., Zapotecas-Martínez S.Fuentes:scopusOn the low-discrepancy sequences and their use in MOEA/D for high-dimensional objective spaces
Conference ObjectAbstract: In spite of the success of the multi-objective evolutionary algorithm based on decomposition (MOEA/DPalabras claves:Autores:Coello Coello C.A., Hernán E. Aguirre, Tanaka K., Zapotecas-Martínez S.Fuentes:scopusUsing a family of curves to approximate the pareto front of a multi-objective optimization problem
ArticleAbstract: The design of selection mechanisms based on quality assessment indicators has become one of the mainPalabras claves:Autores:Coello Coello C.A., Hernán E. Aguirre, Sosa Hernández V.A., Tanaka K., Zapotecas-Martínez S.Fuentes:scopus