ДЕЯКІ ПІДХОДИ ДО РЕГУЛЯРИЗАЦІЇ НЕЛІНІЙНИХ ЗАДАЧ ОПТИМІЗАЦІЇ
Methods for transformation of convex optimization problems with constraints into equivalent problems with better computational properties are considered. Main attention is paid to conical approximations and conical extensions of the objective functions from the feasible set to the full space of vari...
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| Datum: | 2025 |
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| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | English |
| Veröffentlicht: |
V.M. Glushkov Institute of Cybernetics of NAS of Ukraine
2025
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| Online Zugang: | https://jais.net.ua/index.php/files/article/view/568 |
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| Назва журналу: | Problems of Control and Informatics |
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Problems of Control and Informatics| Zusammenfassung: | Methods for transformation of convex optimization problems with constraints into equivalent problems with better computational properties are considered. Main attention is paid to conical approximations and conical extensions of the objective functions from the feasible set to the full space of variables. As a result we get an unconstrainerd (regularized) convex programming problem, whose solution coincides with the solution of the initial one. Special importance these approaches have in the case when the objective function is not defined outside of the feasible set. Effective procedures for computation of auxiliary functions are proposed, peculiarities of software realizations are considered, results of computational experiments are reported. |
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