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

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Abstract

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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Acknowledgements

We thank the reviewers for their valuable remarks enabling us to improve the presentation of our results..

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Authors and Affiliations

  1. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Antanas Žilinskas

  2. Institute of Computer Science, Vilnius University, Vilnius, Lithuania

    Linas Litvinas

Authors
  1. Antanas Žilinskas
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  2. Linas Litvinas
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Correspondence to Antanas Žilinskas.

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The authors declare that they have no conflict of interests.

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Communicated by Yaroslav D. Sergeyev.

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Žilinskas, A., Litvinas, L. A hybrid of the simplicial partition-based Bayesian global search with the local descent. Soft Comput 24, 17601–17608 (2020). https://doi.org/10.1007/s00500-020-05095-0

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