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Optimization
A Journal of Mathematical Programming and Operations Research
Volume 65, 2016 - Issue 6
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Articles

A unifying theory of exactness of linear penalty functions

M. V. DolgopolikFaculty of Applied Mathematics and Control Processes, Saint Petersburg State University, Saint Petersburg, Russia.;Institute of Problems in Mechanical Engineering, Russian Academy of Sciences, Saint Petersburg, Russia.Correspondence[email protected]
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Pages 1167-1202 | Received 12 May 2015, Accepted 22 Oct 2015, Published online: 22 Dec 2015

Citations (19)

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Read on this site (3)

M. V. Dolgopolik. (2023) Steering exact penalty DCA for nonsmooth DC optimisation problems with equality and inequality constraints. Optimization Methods and Software 38:4, pages 668-697.
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M. V. Dolgopolik. (2022) Exact augmented Lagrangians for constrained optimization problems in Hilbert spaces I: theory. Optimization 0:0, pages 1-41.
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M. V. Dolgopolik. (2017) A unifying theory of exactness of linear penalty functions II: parametric penalty functions. Optimization 66:10, pages 1577-1622.
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Articles from other publishers (16)

M. V. Dolgopolik. (2023) DC semidefinite programming and cone constrained DC optimization II: local search methods. Computational Optimization and Applications 85:3, pages 993-1031.
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A. V. Fominyh. (2022) The subdifferential descent method in a nonsmooth variational problem. Optimization Letters 17:3, pages 675-698.
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M. V. Dolgopolik. (2021) Exact penalty functions with multidimensional penalty parameter and adaptive penalty updates. Optimization Letters 16:4, pages 1281-1300.
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M. V. Dolgopolik. 2022. High-Dimensional Optimization and Probability. High-Dimensional Optimization and Probability 185 218 .
A. V. Fominyh. (2021) The quasidifferential descent method in a control problem with nonsmooth objective functional. Optimization Letters 15:8, pages 2773-2792.
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A. S. Strekalovsky. 2021. Mathematical Optimization Theory and Operations Research. Mathematical Optimization Theory and Operations Research 17 31 .
M. V. Dolgopolik. (2019) Metric Regularity of Quasidifferentiable Mappings and Optimality Conditions for Nonsmooth Mathematical Programming Problems. Set-Valued and Variational Analysis 28:3, pages 427-449.
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Gulcin Dinc Yalcin & Refail Kasimbeyli. (2020) On weak conjugacy, augmented Lagrangians and duality in nonconvex optimization. Mathematical Methods of Operations Research 92:1, pages 199-228.
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Anurag Jayswal & Preeti. (2020) An exact minimax penalty function approach to solve multitime variational problems. RAIRO - Operations Research 54:3, pages 637-652.
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M. V. Dolgopolik. (2020) Exact penalty functions for optimal control problems II: Exact penalization of terminal and pointwise state constraints. Optimal Control Applications and Methods 41:3, pages 898-947.
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M. V. Dolgopolik. (2019) New global optimality conditions for nonsmooth DC optimization problems. Journal of Global Optimization 76:1, pages 25-55.
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M.V. Dolgopolik & A.V. Fominyh. (2019) Exact penalty functions for optimal control problems I: Main theorem and free‐endpoint problems. Optimal Control Applications and Methods 40:6, pages 1018-1044.
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M. V. Dolgopolik. (2018) Augmented Lagrangian functions for cone constrained optimization: the existence of global saddle points and exact penalty property. Journal of Global Optimization 71:2, pages 237-296.
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M. V. Dolgopolik. (2018) A Unified Approach to the Global Exactness of Penalty and Augmented Lagrangian Functions II: Extended Exactness. Journal of Optimization Theory and Applications 176:3, pages 745-762.
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M. V. Dolgopolik. (2018) A Unified Approach to the Global Exactness of Penalty and Augmented Lagrangian Functions I: Parametric Exactness. Journal of Optimization Theory and Applications 176:3, pages 728-744.
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M. V. Dolgopolik. (2017) Existence of augmented Lagrange multipliers: reduction to exact penalty functions and localization principle. Mathematical Programming 166:1-2, pages 297-326.
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