Decentralised Distributed Multiple Objective Particle Swarm Optimisation Using Peer to Peer Networks
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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.
IEEE Congress on Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence).
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