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Memorias de investigación
Artículos en revistas:
A New Methodology for the Automatic Creation of Adaptive Hybrid Algorithms
Año:2010
Áreas de investigación
  • Inteligencia artificial
Datos
Descripción
Hybrid Evolutionary Algorithms are a promising alternative to deal with the problem of selecting the most appropriate Evolutionary Algorithm for a specific problem. By means of the combination of different heuristic optimization ap- proaches, it is possible to profit from the benefits of the best approach or, even more, to discover synergies between the algorithms that could improve the results of the best performing individual algorithm. Nowadays, there is an active research in the design of dynamic or adaptive combination strategies for hybrid algorithms. However, little research has been done in the automatic learning of the best hy- bridization strategy. This paper proposes a new methodology for developing in- telligent adaptive hybrid algorithms that uses data mining techniques to analyze the results from past executions. The proposed methodology has been evaluated on a well-known benchmark on continuous optimization made up of 19 differ- ent functions and several dimensions (50, 100, 200 and 500). Several analyses have been conducted and statistical tests have been used for validating the results. The generated hybrid algorithm has achieved outstanding results, obtaining signif- icantly better results than the MOS algorithm, the most performant algorithm on this benchmark, and the CMA-ES algorithm, one of the reference algorithms in continuous optimization.
Internacional
Si
JCR del ISI
Si
Título de la revista
Intelligent Data Analysis
ISSN
1088-467X
Factor de impacto JCR
0,929
Información de impacto
Volumen
16
DOI
Número de revista
1
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Participantes
  • Autor: Santiago Muelas Pascual (UPM)
  • Autor: Antonio Latorre De la Fuente (UPM)
  • Autor: Jose Maria Peña Sanchez (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: COMPUTATIONAL INTELLIGENCE GROUP
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