Autor(es):
Rocha, Ana Maria A. C. 
; Costa, M. Fernanda P. ; Fernandes, Edite Manuela da G. P.
Data: 2012
Identificador Persistente: http://hdl.handle.net/1822/20039
Origem: RepositóriUM - Universidade do Minho
Assunto(s): Global optimization; Swarm Intelligence; Artificial Fish Swarm; Filter Method
Descrição
Ana Maria A.C. Rocha, M. Fernanda P. Costa and Edite M.G.P. Fernandes, An Artificial Fish Swarm Filter-Based Method for Constrained Global Optimization, B. Murgante, O. Gervasi, S. Mirsa, N. Nedjah, A.M. Rocha, D. Taniar, B. Apduhan (Eds.), Lecture Notes in Computer Science, Part III, LNCS 7335, pp. 57–71, Springer, Heidelberg, 2012. An artificial fish swarm algorithm based on a filter methodology
for trial solutions acceptance is analyzed for general constrained
global optimization problems. The new method uses the filter set concept
to accept, at each iteration, a population of trial solutions whenever
they improve constraint violation or objective function, relative to the
current solutions. The preliminary numerical experiments with a wellknown
benchmark set of engineering design problems show the effectiveness
of the proposed method.
