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Optimization
A Journal of Mathematical Programming and Operations Research
Volume 71, 2022 - Issue 4: Special issue dedicated to the 80th birthday of Professor Alexander Rubinov
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Articles

Zero duality gap conditions via abstract convexity

Hoa T. Buia ARC Centre for Transforming Maintenance through Data Science and School of Electrical Engineering, Computing, and Mathematical Sciences, Curtin University, Bentley, AustraliaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-1698-6383View further author information
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Regina S. Burachikb Mathematics, STEM University of South Australia, Adelaide, AustraliaORCID Iconhttps://orcid.org/0000-0003-1332-6213View further author information
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Alexander Y. Krugerc School of Engineering, Information Technology and Physical Science, Federation University Australia, Ballarat, AustraliaORCID Iconhttps://orcid.org/0000-0002-7861-7380View further author information
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David T. Yostc School of Engineering, Information Technology and Physical Science, Federation University Australia, Ballarat, AustraliaORCID Iconhttps://orcid.org/0000-0003-2275-8579View further author information
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Pages 811-847 | Received 12 Sep 2020, Accepted 19 Mar 2021, Published online: 10 Apr 2021

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Read on this site (4)

Elimhan N. Mahmudov. (2024) Optimization of first-order Nicoletti boundary value problem with discrete and differential inclusions and duality. Optimization 73:3, pages 899-923.
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Valentin V. Gorokhovik. (2023) Regularly abstract convex functions with respect to the set of Lipschitz continuous concave functions. Optimization 72:1, pages 241-261.
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Ewa Bednarczuk & The Hung Tran. (2023) Duality for composite optimization problem within the framework of abstract convexity. Optimization 72:1, pages 37-80.
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N. Dinh, M. A. Goberna, M. A. López-Cerdá & M. Volle. (2023) Relaxed Lagrangian duality in convex infinite optimization: reducibility and strong duality. Optimization 72:1, pages 189-214.
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Articles from other publishers (4)

Emanuel Laude, Andreas Themelis & Panagiotis Patrinos. (2023) Dualities for Non-Euclidean Smoothness and Strong Convexity under the Light of Generalized Conjugacy. SIAM Journal on Optimization 33:4, pages 2721-2749.
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Hartmut Bauermeister, Emanuel Laude, Thomas Möllenhoff, Michael Moeller & Daniel Cremers. (2022) Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields. SIAM Journal on Imaging Sciences 15:3, pages 1253-1281.
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V. V. Gorokhovik & A. S. Tykoun. (2022) The subdifferentiability of functions convex with respect to the set of Lipschitz concave functions. Proceedings of the National Academy of Sciences of Belarus. Physics and Mathematics Series 58:1, pages 7-20.
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Ewa M. Bednarczuk & Monika Syga. (2021) On duality for nonconvex minimization problems within the framework of abstract convexity. Optimization 71:4, pages 949-971.
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