Title :
A Performance Analysis of Mono and Multi-objective Evolutionary Algorithms Assisted by Meta-modeling
Author :
Brito, Leonardo Da Cunha ; Macedo, Ciro José A ; Rocha, Adson Silva ; de Carvalho, P.H.P.
Author_Institution :
Escola de Eng. Eletr. e de Comput., Univ. Fed. de Goias, Goiania, Brazil
Abstract :
Evolutionary Algorithms can be inefficient in optimizing problems in which fitness evaluation of candidate solutions is computationally expensive. In this paper, single and multi-objective evolutionary methods assisted by meta-models are proposed and analyzed. Meta-models are used to identify promising regions of search space in order to save evaluations of objective-functions. The meta-models are produced using regularized Radial Basis Functions networks. The study in this work shows that the method assisted by meta-modeling accelerates the convergence of the evolutionary process in mono and multi-objectives optimizations.
Keywords :
evolutionary computation; optimisation; radial basis function networks; meta modeling; monoobjective evolutionary algorithm; multiobjective evolutionary algorithm; optimization problem; regularized radial basis functions network; search space; Approximation methods; Convergence; Evolutionary computation; Indexes; Metamodeling; Optimization; Radial basis function networks; Evolutionary Algorithhms; Meta-modeling;
Conference_Titel :
Neural Networks (SBRN), 2010 Eleventh Brazilian Symposium on
Conference_Location :
Sao Paulo
Print_ISBN :
978-1-4244-8391-4
Electronic_ISBN :
1522-4899
DOI :
10.1109/SBRN.2010.37
