Asynchronous Multi-objective Optimisation in Unreliable Distributed Environments

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Title Asynchronous Multi-objective Optimisation in Unreliable Distributed Environments
Author Lewis, Andrew; Mostaghim, Sanaz; Scriven, Ian
Book Title Biologically-inspired Optimisation Methods: Parallel Algorithms, Systems and Applications
Editor A. Lewis, S. Mostaghim and M. Randall
Year Published 2009
Place of publication Berlin
Publisher Springer-Verlag
Abstract This chapter examines the performance characteristics of both asynchronous and synchronous parallel particle swarm optimisation algorithms in heterogeneous, fault-prone environments. The chapter starts with a simple parallelisation paradigm, the Master-Slave model using Multi-Objective Particle Swarm Optimisation (MOPSO) in a heterogeneous environment. Extending the investigation to general, distributed environments, algorithm convergence is measured as a function of both iterations completed and time elapsed. Asynchronous particle updates are shown to perform comparably to synchronous updates 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. Finally, the issue of how to utilise newly available nodes, as well as the loss of existing nodes, is considered and two methods of generating new particles during algorithm execution are investigated.
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Copyright Statement Copyright 2009 Springer. This is the author-manuscript version of this paper. It is reproduced here in accordance with the copyright policy of the publisher. Please refer to the publisher’s website for further information.
Chapter Number 3
Page from 51
Page to 78
ISBN 978-3-642-01261-7
Date Accessioned 2009-09-21
Language en_US
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Distributed and Grid Systems; Optimisation
Publication Type Book Chapters
Publication Type Code b1

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