DocumentCode
2916323
Title
Decentralised distributed multiple objective particle swarm optimisation using peer to peer networks
Author
Scriven, Ian ; Lewis, Andrew ; Ireland, David ; Lu, Junwei
Author_Institution
Sch. of Eng., Griffith Univ., Brisbane, QLD
fYear
2008
fDate
1-6 June 2008
Firstpage
2925
Lastpage
2928
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.
Keywords
multivariable systems; particle swarm optimisation; peer-to-peer computing; decentralised distributed multiple objective particle swarm optimisation; fault-tolerent operation; objective-space knowledge; peer-to-peer computer networks; staggered propagation; Algorithm design and analysis; Computer networks; Distributed computing; Genetic algorithms; Grid computing; Master-slave; Particle swarm optimization; Peer to peer computing; Performance analysis; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-1822-0
Electronic_ISBN
978-1-4244-1823-7
Type
conf
DOI
10.1109/CEC.2008.4631191
Filename
4631191
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