Lipschitzian optimization without the Lipschitz constant
Journal of Optimization Theory and Applications
Journal of Global Optimization
Constrained Global Optimization of Expensive Black Box Functions Using Radial Basis Functions
Journal of Global Optimization
A particle swarm pattern search method for bound constrained global optimization
Journal of Global Optimization
pCMALib: a parallel fortran 90 library for the evolution strategy with covariance matrix adaptation
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Stochastic ranking for constrained evolutionary optimization
IEEE Transactions on Evolutionary Computation
Parallel Parameter Identification in Industrial Biotechnology
ISPA '12 Proceedings of the 2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications
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Real-valued black-box optimization of badly behaved and not well understood functions is a wide topic in many scientific areas. Possible applications range from maximizing portfolio profits in financial mathematics over efficient training of neuronal networks in computational linguistics to parameter identification of metabolism models in industrial biotechnology. This paper presents a comparison of several global as well as local optimization strategies applied to the task of efficiently identifying free parameters of a metabolic network model. A focus is being set on the ease of adapting these strategies to modern, highly parallel architectures. Finally an outlook on the possible parallel performance is being presented.