Parallel Evolutionary Optimization of Multibody Systems with Application to Railway Dynamics

The optimization of multibody systems usually requires many costlycriteria computations since the equations of motion must be evaluated bynumerical time integration for each considered design. For activelycontrolled or flexible multibody systems additional difficulties ariseas the criteria may contain non-differentiable points or many localminima.Therefore, in this paper a stochastic evolution strategy is used incombination with parallel computing in order to reduce the computationtimes whilst keeping the inherent robustness. For the parallelization amaster-slave approach is used in a heterogeneous workstation/PCcluster. The pool-of-tasks concept is applied in order to deal withthe frequently changing workloads of different machines in the cluster.In order to analyze the performance of the parallel optimizationmethod, the suspension of an ICE passenger coach, modelled as an elasticmultibody system, is optimized simultaneously with regard to severalcriteria including vibration damping and a criterion related to safetyagainst derailment. The iterative and interactive nature of a typicaloptimization process for technical systems is emphasized.