Mostrando 10 resultados de: 17
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(3)
GECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference Companion(2)
2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings(1)
2006 IEEE Congress on Evolutionary Computation, CEC 2006(1)
2016 IEEE Congress on Evolutionary Computation, CEC 2016(1)
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Programación informática, programas, datos, seguridad(8)
Métodos informáticos especiales(6)
Ciencias de la computación(4)
Biología(3)
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scopus(17)
Closed state model for understanding the dynamics of MOEAs
Conference ObjectAbstract: This work proposes the use of simple closed state models to capture, analyze and compare the dynamicPalabras claves:empirical study, Genetic Algorithms, multi-objective optimization, Working principles of evolutionary computingAutores:Derbel B., Hernán E. Aguirre, Liefooghe A., Monzón H., Tanaka K., Verel S.Fuentes:scopusAn effective EA for short term evolution with small population for traffic signal optimization
Conference ObjectAbstract: In this work, we study the effects of mutation operators combined with a varying mutation schedule aPalabras claves:Autores:Daolio F., Hernán E. Aguirre, Rolando Armas, Tanaka K.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:scopusAdvances on many-objective evolutionary optimization
Conference ObjectAbstract:Palabras claves:Autores:Hernán E. AguirreFuentes:scopusDynamic control of the number of crossed genes in evolutionary many-objective optimization
Conference ObjectAbstract: When multi-objective evolutionary algorithms (MOEAs) are applied to many-objective optimization probPalabras claves:Autores:Coello Coello C.A., Hernán E. Aguirre, Sato H., Tanaka K.Fuentes:scopusEffects of population size on selection and scalability in evolutionary many-objective optimization
Conference ObjectAbstract: In this work we study population size as a fraction of the true Pareto optimal set and analyze its ePalabras claves:Autores:Hernán E. Aguirre, Liefooghe A., Tanaka K., Verel S.Fuentes:scopusEffects of δ-similar elimination and controlled elitism in the NSGA-II multiobjective evolutionary algorithm
Conference ObjectAbstract: In this paper, we propose δ-similar elimination to induce a better distribution of non-dominated solPalabras claves:Autores:Hernán E. Aguirre, Sato M., Tanaka K.Fuentes:scopusGenetic diversity and effective crossover in evolutionary many-objective optimization
Conference ObjectAbstract: In this work, we analyze genetic diversity of Pareto optimal solutions (POS) and study effective croPalabras claves:Autores:Hernán E. Aguirre, Sato H., Tanaka K.Fuentes:scopusRandom bit climbers on multiobjective MNK-landscapes: Effects of memory and population climbing
Conference ObjectAbstract: In this work we give an extension of Kauffman's NK-Landscapes to multiobjective MNK-Landscapes in orPalabras claves:Epistasis, Evolutionary algorithms, Multiobjective MNK-Landscapes, Non-linear fitness functions, Population climbing, Random bit climbersAutores:Hernán E. Aguirre, Tanaka K.Fuentes:scopusRoles of CCG crossover and mutation in evolutionary many-objective optimization
Conference ObjectAbstract: When we solve many-objective optimization problems (MaOPs) by using multi-objective evolutionary algPalabras claves:Autores:Hernán E. Aguirre, Sato H., Tanaka K.Fuentes:scopus