Decentralised Distributed Multiple Objective Particle Swarm Optimisation Using Peer to Peer Networks

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Author(s)
Scriven, Ian
Lewis, Andrew
Ireland, David
Lu, Junwei
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Michalewicz and Reynolds

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2008
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142910 bytes

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Hong Kong, PEOPLES R CHINA

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Abstract

This paper describes a distributed particle swarm optimisation algorithm (PSO) based on peer-to-peer computer networks. A number of modifications are made to the more traditional synchronous PSO algorithm to allow for fully decentralised, scalable and fault-tolerent operation. The modified algorithm uses staggered propagation of objective-space knowledge between sub-swarms to eliminate the need for a centralised data store. Analytical test functions are used to examine the performance of the proposed algorithm and its variations in comparison with a basic synchronous PSO implementation. The results clearly show the feasibility of decentralised particle swarm optimisation.

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2008 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-8

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© 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

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