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

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Title: A hybrid of the simplicial partition-based Bayesian global search with the local descent.
Authors: Žilinskas, Antanas1 (AUTHOR) antanas.zilinskas@mif.vu.lt, Litvinas, Linas2 (AUTHOR)
Source: Soft Computing - A Fusion of Foundations, Methodologies & Applications. Dec2020, Vol. 24 Issue 23, p17601-17608. 8p.
Subjects: Global optimization, Algorithms, Mathematical optimization, Computational complexity
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. [ABSTRACT FROM AUTHOR]
Copyright of Soft Computing - A Fusion of Foundations, Methodologies & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: A hybrid of the simplicial partition-based Bayesian global search with the local descent.
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  Data: 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. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Soft Computing - A Fusion of Foundations, Methodologies & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s00500-020-05095-0
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      – SubjectFull: Mathematical optimization
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      – SubjectFull: Computational complexity
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      – TitleFull: A hybrid of the simplicial partition-based Bayesian global search with the local descent.
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              Text: Dec2020
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