Ponencia
Noiseless Functions Black-Box Optimization: Evaluation of a Hybrid Particle Swarm with Differential Operators
Autor/es | García Nieto, José Manuel
Alba, Enrique Apolloni, Javier |
Departamento | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial |
Fecha de publicación | 2009 |
Fecha de depósito | 2021-05-11 |
Publicado en |
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ISBN/ISSN | 978-1-60558-505-5 |
Resumen | In this work we evaluate a Particle Swarm Optimizer hy-
bridized with Di®erential Evolution and apply it to the Black-
Box Optimization Benchmarking for noiseless functions (BBOB
2009). We have performed the complete ... In this work we evaluate a Particle Swarm Optimizer hy- bridized with Di®erential Evolution and apply it to the Black- Box Optimization Benchmarking for noiseless functions (BBOB 2009). We have performed the complete procedure estab-lished in this special session dealing with noiseless functions with dimension: 2, 3, 5, 10, 20, and 40 variables. Our pro-posal obtained an accurate level of coverage rate, despite the simplicity of the model and the relatively small number of function evaluations used. |
Agencias financiadoras | Ministerio de Ciencia e Innovación (MICIN). España Junta de Andalucía |
Identificador del proyecto | TIN2008-06491-C04-01
P07-TIC-03044 |
Cita | García Nieto, J.M., Alba, E. y Apolloni, J. (2009). Noiseless Functions Black-Box Optimization: Evaluation of a Hybrid Particle Swarm with Differential Operators. En GECCO 2009: 11th annual conference on Genetic and evolutionary computation (2231-2238), Montreal Québec Canada: ACM Digital Library. |
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