2008
DOI: 10.2174/1874110x00802010173
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Particle Swarms and Nonextensive Statistics for Nonlinear Optimisation

Abstract: Particle swarm methods are inspired from the dynamics of social interaction and employ information sharing to seek solutions to difficult optimisation problems. In this paper we introduce an approach that combines ideas from particle swarm optimisation (PSO) and the theory of nonextensive statistical mechanics. We develop two algorithms that adopt this approach and conduct an experimental study using benchmark functions to investigate their effectiveness in nonlinear optimisation. Results appear to be promisin… Show more

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Cited by 3 publications
(1 citation statement)
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“…The system is sub-extensive when q > 1 and, for q < 1, it is super-extensive [14,15].Özeren [8] studied nonextensive quantum characteristics of the generalized CK oscillator in connection with SU(1,1) coherent states, on the basis of exactly the same Hamiltonian given in Eq. (7) (except for disregarding a trivial factor δ).…”
Section: Hamiltonian Dynamics Of Fieldsmentioning
confidence: 99%
“…The system is sub-extensive when q > 1 and, for q < 1, it is super-extensive [14,15].Özeren [8] studied nonextensive quantum characteristics of the generalized CK oscillator in connection with SU(1,1) coherent states, on the basis of exactly the same Hamiltonian given in Eq. (7) (except for disregarding a trivial factor δ).…”
Section: Hamiltonian Dynamics Of Fieldsmentioning
confidence: 99%