Improving the algorithmic efficiency and performance of channel-based evolutionary algorithms
| Autor: | Mario García Valdez, Sergio Rojas-Galeano, Juan Luis Jiménez Laredo, Pedro A. Castillo, Juan-Julián Merelo Guervós |
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| Přispěvatelé: | Departamento de Arquitectura y tecnología de computadores, Universidad de Granada (UGR), Equipe Réseaux d'interactions et Intelligence Collective (RI2C - LITIS), Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes (LITIS), Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Université Le Havre Normandie (ULH), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Normandie Université (NU), Instituto Tecnológico de Tijuana, Instituto Tecnológico de Tijuana [Tijuana], District University of Bogotá |
| Rok vydání: | 2019 |
| Předmět: |
Computer science
Distributed computing Evolutionary algorithm 0102 computer and information sciences 02 engineering and technology [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE] 01 natural sciences [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] 010201 computation theory & mathematics Algorithmic efficiency Scalability 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing [INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC] ComputingMilieux_MISCELLANEOUS |
| Zdroj: | GECCO (Companion) Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2019 Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2019, Jul 2019, Prague, Czech Republic |
| Popis: | Concurrent evolutionary algorithms use threads that communicate via messages. Parametrizing the work in every thread and the way they communicate results is a major challenge in its design. In this paper we work with concurrent evolutionary algorithms implemented in Perl 6, and explore different options of single-thread evolution parametrization, communication and mixing of results, showing that scalability is achieved in a multi-core environment. |
| Databáze: | OpenAIRE |
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