A hybrid of the simplicial partition-based Bayesian global search with the local descent

We propose a global optimization algorithm hybridizing a version of Bayesian global search with local minimization. The implementation of Bayesian algorithm is based on the simplician partition of the feasible region. Our implementation is free from the typical computational complexity of the standard implementations of Bayesian algorithms. The local minimization counterpart improves the efficiency of search in the indicated potential basins of global minimum. The performance of the proposed algorithm is illustrated by the results of a numerical experiment.

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