Normal view MARC view ISBD view

GAAP. Genetic algorithm with auxiliary populations applied to continuous optimization problems

By:

Corbalán, Leonardo César

Contributor(s):

Material type: Article

ArticleDescription: 1 archivo (154,9 KB)Subject(s):

OPTIMIZACIÓN

Online resources:

Click here to access online

Summary: Genetic algorithms have been used successfully to solve continuous optimization problems. However, an early convergence to low-quality solutions is one of the most common difficulties encountered when using these strategies. In this paper, a method that combines multiple auxiliary populations with the main population of the algorithm is proposed. The role of the auxiliary populations is dual: to prevent or hinder the early convergence to local suboptimal solutions, and to provide a local search mechanism for a greater exploitation of the most promising regions within the search space.

Average rating: 0.0 (0 votes)

Holdings ( 1 )
Title notes ( 3 )

Holdings
Item type	Home library	Collection	Call number	URL	Status	Date due	Barcode
Capítulo de libro	Biblioteca de la Facultad de Informática	Biblioteca digital	A0295 (Browse shelf(Opens below))	Link to resource	No corresponde

Browsing Biblioteca de la Facultad de Informática shelves, Collection: Biblioteca digital Close shelf browser (Hides shelf browser)

Previous								Next
Previous	A0292 Games as educational strategy : A case of tangible interaction for users of alternative and augmentative communication	A0293 Crowdsourcing mobile web applications	A0294 Passive analog filter design using GP population control strategies	A0295 GAAP. Genetic algorithm with auxiliary populations applied to continuous optimization problems	A0296 Resources neurosearch in peer-to-peer networks	A0297 Juegos educativos móviles basados en posicionamiento : una guía para su conceptualización	A0298 Integrando trazabilidad a la generación de casos de prueba del sistema : Una propuesta MDD/MBT	Next

Formato de archivo: PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca)

Genetic algorithms have been used successfully to solve continuous optimization problems. However, an early convergence to low-quality solutions is one of the most common difficulties encountered when using these strategies. In this paper, a method that combines multiple auxiliary populations with the main population of the algorithm is proposed. The role of the auxiliary populations is dual: to prevent or hinder the early convergence to local suboptimal solutions, and to provide a local search mechanism for a greater exploitation of the most promising regions within the search space.

International Conference on Information Technology Interfaces (34ª : 2012 jun. 25-28 : Cavtat, Croacia). Proceedings. IEEE, 2012, pp. 411-416