GAAP. Genetic algorithm with auxiliary populations applied to continuous optimization problems
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ArticleDescription: 1 archivo (154,9 KB)Subject(s): Online resources: 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.
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Biblioteca de la Facultad de Informática | Biblioteca digital | A0295 (Browse shelf(Opens below)) | Link to resource | No corresponde |
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