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Parallel and Distributed Processing Symposium, International (2008)
Miami, FL, USA
Apr. 14, 2008 to Apr. 18, 2008
ISBN: 978-1-4244-1693-6
pp: 1-8
Antonio J. Nebro , Departamento de Lenguajes y Ciencias de la Computación, E.T.S.I. Informática, Universidad de Málaga, Spain
Enrique Alba , Departamento de Lenguajes y Ciencias de la Computación, E.T.S.I. Informática, Universidad de Málaga, Spain
Francisco Luna , Departamento de Lenguajes y Ciencias de la Computación, E.T.S.I. Informática, Universidad de Málaga, Spain
Juan J. Durillo , Departamento de Lenguajes y Ciencias de la Computación, E.T.S.I. Informática, Universidad de Málaga, Spain
ABSTRACT
Many of the optimization problems from the real world are multiobjective in nature, and the reference algorithm for multiobjective optimization is NSGA-II. Frequently, these problems present a high complexity, so classical metaheuristic algorithms fail to solve them in a reasonable amount of time; in this context, parallelism is a choice to overcome this fact to some extent. In this paper we study three parallel approaches (a synchronous and two asynchronous strategies) for the NSGA-II algorithm based on the master-worker paradigm. The asynchronous schemes are designed to be used in grid systems, so they can make use of hundreds of machines. We have applied them to solve a real world problem which lies in optimizing a broadcasting protocol using a network simulator. Our experiences reveal that significant time reductions can be achieved with the distributed approaches by using a grid system of more than 300 processors.
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CITATION
Antonio J. Nebro, Enrique Alba, Francisco Luna, Juan J. Durillo, "A study of master-slave approaches to parallelize NSGA-II", Parallel and Distributed Processing Symposium, International, vol. 00, no. , pp. 1-8, 2008, doi:10.1109/IPDPS.2008.4536375
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