variavel0=<b>FABIANO L. DE SOUSA</b> - fabiano@dem.inpe.br INPE
<b>Valeri Vlassov</b> - vlassov@dem.inpe.br INPE
<b>Fernando Manuel Ramos</b> - fernando@lac.inpe.br INPE
<b>Abstract.</b> In this paper an application of the Generalized Extremal Optimization (GEO) algorithm to the optimization of a heat pipe (HP) for a space application is presented. The GEO algorithm is a generalization of the Extremal Optimization (EO) algorithm, devised to be applied readily to a broad class of design optimization problems, regardless of the design space complexity it would face. It is of easy implementation, does not make use of derivatives and can be applied to either unconstrained or constrained problems with continuous, discrete or integer variables. The GEO algorithm has been tested in a series of test functions, showing to be competitive to other stochastic algorithms such as the Genetic Algorithm. In this work it is applied to the problem of minimizing the mass of a HP as a function of a desirable heat transport capability and a given temperature on the condenser. The optimal solutions were obtained for different heat loads, heat sink temperatures and three working fluids: ammonia, methanol and ethanol. The present design application highlights the GEO features of being easily implemented and efficient on tackling optimization problems where the objective function presents design variables with strong non-linear interactions and is subject to multiple constraints.
<b>Keywords.</b> Self-organized criticality, optimization, optimal design, heat pipe.