Author(s):
Rocha, Ana Maria A. C. 
; Costa, M. Fernanda P. ; Fernandes, Edite Manuela da G. P.
Date: 2012
Persistent ID: http://hdl.handle.net/1822/20039
Origin: RepositóriUM - Universidade do Minho
Subject(s): Global optimization; Swarm Intelligence; Artificial Fish Swarm; Filter Method
Description
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.
