A new projective exact penalty function for a general constrained optimization
A new projective exact penalty function method is proposed for the equivalent reduction of constrained optimization problems to unconstrained ones. In the method, the original objective function is extended to infeasible points by summing its value at the projection of an infeasible point on the f...
Збережено в:
| Дата: | 2022 |
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| Автор: | |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
Видавничий дім "Академперіодика" НАН України
2022
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| Назва видання: | Доповіді НАН України |
| Теми: | |
| Онлайн доступ: | http://dspace.nbuv.gov.ua/handle/123456789/187186 |
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| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Цитувати: | A new projective exact penalty function for a general constrained optimization / V.I. Norkin // Доповіді Національної академії наук України. — 2022. — № 5. — С. 23-29. — Бібліогр.: 14 назв. — англ. |
Репозитарії
Digital Library of Periodicals of National Academy of Sciences of Ukraine| Резюме: | A new projective exact penalty function method is proposed for the equivalent reduction of constrained
optimization problems to unconstrained ones. In the method, the original objective function is extended to
infeasible points by summing its value at the projection of an infeasible point on the feasible set with the
distance to the set. The equivalence means that local and global minimums of the problems coincide. Nonconvex
sets with multivalued projections are admitted, and the objective function may be lower semicontinuous. The
particular case of convex problems is included. So the method does not assume the existence of the objective
function outside the allowable area and does not require the selection of the penalty coefficient. |
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