Characterizations of the solution set for tangentially convex optimization problems
In convex optimization problems, characterizations of the solution set in terms of the classical subdifferentials have been investigated by Mangasarian. In quasiconvex optimization problems, characterizations of the solution set for quasiconvex programming in terms of the Greenberg–Pierskalla subdif...
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Veröffentlicht in: | Optimization letters 2023-05, Vol.17 (4), p.1027-1048 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In convex optimization problems, characterizations of the solution set in terms of the classical subdifferentials have been investigated by Mangasarian. In quasiconvex optimization problems, characterizations of the solution set for quasiconvex programming in terms of the Greenberg–Pierskalla subdifferentials were given by Suzuki and Kuroiwa. In this paper, our attention focuses on the class of tangentially convex functions. Indeed, we study characterizations of the solution set for tangentially convex optimization problems in terms of subdifferentials. For this purpose, we use tangential subdifferentials and the Greenberg-Pierskalla subdifferentials and present necessary and sufficient optimality conditions for tangentially convex optimization problems. As a consequence, we investigate characterizations of the solution set in terms of tangential subdifferentials and the Greenberg–Pierskalla subdifferentials for tangentially convex optimization problems. Moreover, we compare our results with previous ones. |
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ISSN: | 1862-4472 1862-4480 |
DOI: | 10.1007/s11590-022-01911-8 |