Method for False Extrema Localization in Global Optimization
The problem of finding the global minimum of a nonnegative function on a positive parallelepiped in n -dimensional Euclidean space is considered. A method for localizing false extrema in a bounded domain near the origin is proposed, which allows one to separate the global minimum from the false ones...
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Veröffentlicht in: | Doklady. Mathematics 2023-08, Vol.108 (1), p.309-311 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | The problem of finding the global minimum of a nonnegative function on a positive parallelepiped in
n
-dimensional Euclidean space is considered. A method for localizing false extrema in a bounded domain near the origin is proposed, which allows one to separate the global minimum from the false ones by moving the former away from the latter. With a suitable choice of the starting point in the gradient descent method, it is possible to prove the convergence of the iterative sequence to the global minimum of the function. |
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ISSN: | 1064-5624 1531-8362 |
DOI: | 10.1134/S1064562423700850 |