Abstract-
For centuries engineers have saught inspirations from nature in designing their
creations. Along with the immitation of biological forms we may consider the
implementation of bio-inspired algorithms for optimizing engineering designs. In
this talk we present a unifying stochastic optimization framework for these
algorithms and we identify their advantages and drawbacks. We discuss their
suitability for flow optimization by presenting examples from their application
to aerodynamic drag reduction, mixing enhancement and to the multiobjective
optimization of turbomachinery components.
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