Generalized extremal optimization: An application in heat pipe design

Abstract In this paper a recently proposed new stochastic method developed to tackle optimization problems with complex design spaces is presented. Called generalized extremal optimization (GEO), it is of easy implementation, does not make use of derivatives and can be applied to unconstrained or constrained problems, non-convex or disjoint design spaces, with any combination of continuous, discrete or integer variables. It is a global search meta-heuristic, as the Genetic Algorithm and the simulated annealing, but with the a priori advantage of having only one free parameter to adjust. In this article the efficacy of the GEO algorithm on dealing with complex design spaces is illustrated through the application of the method to the design of a heat pipe for satellite thermal control.

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