Mixed and hybrid finite element methods
Mixed and hybrid finite element methods
The controlled random search algorithm in optimizing regression models
Computational Statistics & Data Analysis
Solution of identification problems in computational mechanics --- parallel processing aspects
PARA'10 Proceedings of the 10th international conference on Applied Parallel and Scientific Computing - Volume 2
Material parameter identification with parallel processing and geo-applications
PPAM'11 Proceedings of the 9th international conference on Parallel Processing and Applied Mathematics - Volume Part I
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We describe the application of two global optimization methods, namely of genetic and random search type algorithms in shape optimization. When the so-called fictitious domain approaches are used for the numerical realization of state problems, the resulting minimized function is non-differentiable and stair-wise, in general. Such complicated behaviour excludes the use of classical local methods. Specific modifications of the above-mentioned global methods for our class of problems are described. Numerical results of several model examples computed by different variants of genetic and random search type algorithms are discussed.