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Parallel genetic algorithms: a feasible distributed : Implementation

Ochoa, Claudio et al · SEDICI UNLP · 1996

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Author / responsible party
Ochoa, Claudio et al
Publisher
SEDICI UNLP
Year
1996
Language
Spanish

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Parallel genetic algorithms, models and implementations, attempts to exploit the intrinsically parallel nature of genetic algorithms. By distributing the total population, these models ref1ects a bebaviour nearer to that of natural systems. A variety of parallel computer systems architectures can offer distinct support features for their implementation. Ibis paper shows sorne remarkable characteristics of parallel genetic algorithms, details of a feasible design and their implementation. A1so some results related to the island model are shown. Eje: Redes Neuronales. Algoritmos genéticos Red de Universidades con Carreras en Informática (RedUNCI)

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APA 7

Ochoa, C. E. A. (1996). Parallel genetic algorithms: a feasible distributed: Implementation. SEDICI UNLP. http://sedici.unlp.edu.ar/handle/10915/24166

MLA

Ochoa, Claudio et al. Parallel genetic algorithms: a feasible distributed: Implementation. SEDICI UNLP, 1996. http://sedici.unlp.edu.ar/handle/10915/24166.

Chicago

Ochoa, Claudio et al. 1996. Parallel genetic algorithms: a feasible distributed: Implementation. SEDICI UNLP. http://sedici.unlp.edu.ar/handle/10915/24166.

Harvard

Ochoa, C. E. A. 1996, Parallel genetic algorithms: a feasible distributed: Implementation, SEDICI UNLP, available at: http://sedici.unlp.edu.ar/handle/10915/24166 [Accessed 7 Aug. 2026].

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Title
Parallel genetic algorithms: a feasible distributed : Implementation
Author / contributors
Ochoa, Claudio et al
Publisher
SEDICI UNLP
Publication year
1996
Language
Spanish

Subjects

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Ciencias Informáticas; Algorithms; System architectures; Parallel; Neural nets; ParalIel genetic algoritbms; performance; granularity; island model; migration schemes; interconnectivity
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