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Applications of Parallel Platforms and Models in Evolutionary Multi-Objective Optimization

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Biologically-Inspired Optimisation Methods

Part of the book series: Studies in Computational Intelligence ((SCI,volume 210))

Abstract

This chapter presents a review of modern parallel platforms and the way in which they can be exploited to implement parallel multi-objective evolutionary algorithms. Regarding parallel platforms, a special emphasis is given to global metacomputing which is an emerging form of parallel computing with promising applications in evolutionary (both multi- and singleobjective) optimization. In addition, we present the well-known models to parallelize evolutionary algorithms (i.e., master-slave, island, diffusion and hybrid models) describing some possible strategies to incorporate these models in the context of multi-objective optimization. Since an important concern in parallel computing is performance assessment, the chapter also presents how to apply parallel performance measures in multi-objective evolutionary algorithms taking into consideration their stochastic nature. Finally, we present a selection of current parallel multi-objective evolutionary algorithms that integrate novel strategies to address multi-objective issues.

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Authors and Affiliations

  1. Departamento de Computación, CINVESTAV-IPN (Evolutionary Computation Group), Av. IPN No. 2508, Col. San Pedro Zacatenco, México, D.F. 07360, México

    Antonio López Jaimes & Carlos A. Coello Coello

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  1. Antonio López Jaimes
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  2. Carlos A. Coello Coello
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Editors and Affiliations

  1. Institute for Integrated and Intelligent Systems, Griffith University, Nathan Campus, 4111, Brisbane, Queensland, Australia

    Andrew Lewis

  2. Institut für Angewandte Informatik und Formale Beschreibungsverfahren - AIFB, Universität Karlsruhe, 76128, Karlsruhe, Germany

    Sanaz Mostaghim

  3. Faculty of Business, Technology and Sustainable Development, Bond University, 4229, Gold Coast, Queensland, Australia

    Marcus Randall

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Jaimes, A.L., Coello, C.A.C. (2009). Applications of Parallel Platforms and Models in Evolutionary Multi-Objective Optimization. In: Lewis, A., Mostaghim, S., Randall, M. (eds) Biologically-Inspired Optimisation Methods. Studies in Computational Intelligence, vol 210. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01262-4_2

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  • DOI: https://doi.org/10.1007/978-3-642-01262-4_2

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