A parallel genetic clustering for inverse problems
A parallel global optimization strategy for an ill posed inverse problem in computational mechanics is proposed. It contains a rough recognition of basins of attraction of local minima (clustering) with the use of genetic algorithms. Two levels of parallelism are involved. Basic asymptotic properties of the proposed genetic clustering will be proved. The computational example of the optimal pretractions design in a network structure (hanging roof) will be also shortly described.
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