Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13087/1945
Title: On weak conjugacy, augmented Lagrangians and duality in nonconvex optimization
Authors: Yalçın, Gülçin Dinç
Kasımbeyli, Refail
Keywords: Weak conjugacy
Augmented Lagrangians
Weak subdifferential
Nonconvex analysis
Duality
Issue Date: 2020
Publisher: Springer Heidelberg
Abstract: In this paper, zero duality gap conditions in nonconvex optimization are investigated. It is considered that dual problems can be constructed with respect to the weak conjugate functions, and/or directly by using an augmented Lagrangian formulation. Both of these approaches and the related strong duality theorems are studied and compared in this paper. By using the weak conjugate functions approach, special cases related to the optimization problems with equality and inequality constraints are studied and the zero duality gap conditions in terms of objective and constraint functions, are established. Illustrative examples are provided.
URI: https://doi.org/10.1007/s00186-020-00708-8
https://hdl.handle.net/20.500.13087/1945
ISSN: 1432-2994
1432-5217
Appears in Collections:Makine Mühendisliği Bölümü Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu

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