ParadisEO: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics

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@Article{Cahon:2004:JoH,

• author = "S. Cahon and N. Melab and E. G. Talbi",
• title = "{ParadisEO}: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics",
• journal = "Journal of Heuristics",
• year = "2004",
• volume = "10",
• number = "3",
• pages = "357--380",
• month = may,
• note = "Special Issue: New Advances on Parallel Meta-Heuristics for Complex Problems",
• keywords = "genetic algorithms, genetic programming, metaheuristics, design and code reuse, parallel and distributed models, object-oriented frameworks, performance and robustness",
• ISSN = "1381-1231",
• URL = "https://rdcu.be/cMLxW",
• URL = "https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.538.8149&rep=rep1&type=pdf",
• DOI = "doi:10.1023/B:HEUR.0000026900.92269.ec",
• code_url = "https://nojhan.github.io/paradiseo/",
• size = "24 pages",
• abstract = "We present the ParadisEO white-box object-oriented framework dedicated to the reusable design of parallel and distributed metaheuristics (PDM). ParadisEO provides a broad range of features including evolutionary algorithms (EA), local searches (LS), the most common parallel and distributed models and hybridization mechanisms, etc. This high content and utility encourages its use at European level. ParadisEO is based on a clear conceptual separation of the solution methods from the problems they are intended to solve. This separation confers to the user a maximum code and design reuse. Furthermore, the fine-grained nature of the classes provided by the framework allow a higher flexibility compared to other frameworks. ParadisEO is of the rare frameworks that provide the most common parallel and distributed models. Their implementation is portable on distributed-memory machines as well as on shared-memory multiprocessors, as it uses standard libraries such as MPI, PVM and PThreads. The models can be exploited in a transparent way, one has just to instantiate their associated provided classes. Their experimentation on the radio network design real-world application demonstrate their efficiency.",
• notes = "Laboratoire d'Informatique Fondamentale de Lille, UMR CNRS 8022, Cite Scientifique, 59655 - Villeneuve d'scq Cedex, France",

}

Genetic Programming entries for Sebastien Cahon Nouredine Melab El-Ghazali Talbi

Citations