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2008
IEEE

Asynchronous multiple objective particle swarm optimisation in unreliable distributed environments

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Asynchronous multiple objective particle swarm optimisation in unreliable distributed environments
Abstract— This paper examines the performance characteristics of both asynchronous and synchronous parallel particle swarm optimisation algorithms in heterogeneous, fault-prone environments. Algorithm convergence is measured as a function of both iterations completed and time elapsed, allowing the two particle update mechanisms to be comprehensively evaluated and compared in such an environment. Asynchronous particle updates are shown to negatively impact the convergence speed in regards to iterations completed, however the increased parallel efficiency of the asynchronous model appears to counter this performance reduction, ensuring the asynchronous update mechanism performs comparably to the synchronous mechanism in fault-free environments. When faults are introduced, the synchronous update method is shown to suffer significant performance drops, suggesting that at least partly asynchronous algorithms should be used in real-world environments where faults can regularly occur.
Ian Scriven, David Ireland, Andrew Lewis, Sanaz Mo
Added 29 May 2010
Updated 29 May 2010
Type Conference
Year 2008
Where CEC
Authors Ian Scriven, David Ireland, Andrew Lewis, Sanaz Mostaghim, Jürgen Branke
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