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Computational Super-Resolution: An Odyssey in Harnessing Priors to Enhance Optical Microscopy Resolution. [PDF]
Anal ChemTian W, Chen R, Chen L.
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Modified gradient method for minimization of nonsmooth penalty functions
Journal of Mathematical Sciences, 1994zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Danilin, Yu. M., Nurnazarov, D.
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Journal of Global Optimization, 2019
For nonlinear optimization problems with equality, inequality and bound constraints, the authors consider a family of penalty functions and prove that, under suitable assumptions, which include a so-called weakly generalized Mangasarian-Fromovitz constraint qualification, when the penalty parameter is large enough every local optimal solution ...
Liu, Qian, Xu, Yuqing, Zhou, Yang
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For nonlinear optimization problems with equality, inequality and bound constraints, the authors consider a family of penalty functions and prove that, under suitable assumptions, which include a so-called weakly generalized Mangasarian-Fromovitz constraint qualification, when the penalty parameter is large enough every local optimal solution ...
Liu, Qian, Xu, Yuqing, Zhou, Yang
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Direct search nonsmooth constrained optimization via rounded ℓ1 penalty functions
Optimization Methods and Software, 2020A class of direct search methods for locally minimizing a Lipschitz continuous black-box function f subject to locally Lipschitz constraints is presented.
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Journal of Optimization Theory and Applications, 2015
The authors consider a vector optimization problem (VP) of a locally Lipschitz function with mixed locally Lipschitz constraints and construct an unconstrained problem (P) by using a vector penalty function. They prove that when the penalty parameter is sufficiently large, saddle points of the associated Lagrange vector function provide weak efficient ...
Jayswal, Anurag, Choudhury, Sarita
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The authors consider a vector optimization problem (VP) of a locally Lipschitz function with mixed locally Lipschitz constraints and construct an unconstrained problem (P) by using a vector penalty function. They prove that when the penalty parameter is sufficiently large, saddle points of the associated Lagrange vector function provide weak efficient ...
Jayswal, Anurag, Choudhury, Sarita
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IFAC Proceedings Volumes, 2000
Abstract Some Optimal Control problems can be reduce to problems of Nonlinear Progran1ming. Methods of penalty functions are widely used in Nonlinear Programming. Theorems of the existence of exact penalty parameters for solving of the problems of Nonlinear Programming by the method of exact penalty functions are proved.
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Abstract Some Optimal Control problems can be reduce to problems of Nonlinear Progran1ming. Methods of penalty functions are widely used in Nonlinear Programming. Theorems of the existence of exact penalty parameters for solving of the problems of Nonlinear Programming by the method of exact penalty functions are proved.
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Stochastic penalty function methods for nonsmooth constrained minimization
Journal of Optimization Theory and Applications, 1996zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Gradient-type method for minimization of nonsmooth penalty functions
Cybernetics, 1989Summary: A method is developed for the minimization of exact penalty functions that does not require solving linear or quadratic programming problems. A fairly general procedure for analyzing the rate of convergence of exact penalty methods is proposed.
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Numerical Functional Analysis and Optimization, 2010
This article is concerned with a class of nonsmooth constrained convex optimization in a real Hilbert space. Coupling with the penalty method, we propose an automatic system (AS) and a nonautomatic system (NS) modeled by differential inclusions. Under a suitable assumption on the feasible region and a proper condition on the objective and constrained ...
Wei Bian, Xiaoping Xue
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This article is concerned with a class of nonsmooth constrained convex optimization in a real Hilbert space. Coupling with the penalty method, we propose an automatic system (AS) and a nonautomatic system (NS) modeled by differential inclusions. Under a suitable assumption on the feasible region and a proper condition on the objective and constrained ...
Wei Bian, Xiaoping Xue
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