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Generalized Extremal Optimization for Solving Complex Optimal Design Problems
Fabiano Luis de Sousa1, Valeri Vlassov1, and Fernando Manuel Ramos2
1Instituto Nacional de Pesquisas Espaciais
INPE/DMC
Av. dos Astronautas, 1758
12227-010 São José dos Campos, SP
Brazil
{fabiano,vlassov}@dem.inpe.br
2Instituto Nacional de Pesquisas Espaciais
INPE/LAC
Av. dos Astronautas, 1758
12227-010 São José dos Campos, SP
Brazil
fernando@lac.inpe.br
Abstract. Recently, Boettcher and Percus [1] proposed a new optimization method, called Extremal Optimization (EO), inspired by a simplified model of natural selection developed to show the emergence of Self-Organized Criticality (SOC) in ecosystems [2]. Although having been successfully applied to hard problems in combinatorial optimization, a drawback of the EO is that for each new optimization problem assessed, a new way to define the fitness of the design variables has to be created [2]. Moreover, to our knowledge it has been applied so far to combinatorial problems with no implementation to continuous functions.
LNCS 2723, p. 375 f.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003