Author(s)

W. Jakob, A. Quinte, K.-P. Scherer & H. Eggert

Abstract

Optimization of a micro fluidic component using a parallel evolutionary algorithm and simulation based on discrete element methods W. Jakob, A. Quinte, K.-P. Scherer & H. Eggert Institute for Applied Computer Science, Forschungszentrum Karlsruhe, Germany Abstract In most cases, application of the powerful evolutionary optimizing method is lim- ited to tasks which can manage with short simulation runtimes, e.g. less than one minute. More precise simulations like discrete element methods require much more time of up to 20 minutes and more. This can be solved by a parallelization of the optimization process. The parallel version of our optimization tool GADO (Ge- netic Algorithm for Design Optimization) based on structured populations scales linearly with the number of involved processors and, thus, enables us to handle op- timization based on time-consuming simulation. This paper introduces the parallelization in brief and describes the optimiza- tion task. The micro fluidic component is

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