Smoothing approximation to the lower order exact penalty function for inequality constrained optimization [PDF]
For inequality constrained optimization problem, we first propose a new smoothing method to the lower order exact penalty function, and then show that an approximate global solution of the original problem can be obtained by solving a global solution of ...
Shujun Lian, Nana Niu
doaj +2 more sources
Partial Exactness for the Penalty Function of Biconvex Programming [PDF]
Biconvex programming (or inequality constrained biconvex optimization) is an important model in solving many engineering optimization problems in areas like machine learning and signal and information processing.
Min Jiang, Zhiqing Meng, Rui Shen
doaj +3 more sources
Smooth exact penalty functions II: a reduction to standard exact penalty functions [PDF]
A new class of smooth exact penalty functions was recently introduced by Huyer and Neumaier. In this paper, we prove that the new smooth penalty function for a constrained optimization problem is exact if and only if the standard nonsmooth penalty function for this problem is exact.
M V Dolgopolik
exaly +3 more sources
Automatic decrease of the penalty parameter in exact penalty function methods [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Annick Sartenaer
exaly +5 more sources
A new projective exact penalty function for a general constrained optimization
A new projective exact penalty function method is proposed for the equivalent reduction of constrained optimization problems to unconstrained ones. In the method, the original objective function is extended to infeasible points by summing its value at ...
V.I. Norkin
doaj +1 more source
A new logarithmic penalty function approach for nonlinear constrained optimization problem [PDF]
This paper presents a new penalty function called logarithmic penalty function (LPF) and examines the convergence of the proposed LPF method. Furthermore, the LaGrange multiplier for equality constrained optimization is derived based on the first-order ...
Mansur Hassan , Adam Baharum
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Exact penalty functions with multidimensional penalty parameter and adaptive penalty updates [PDF]
In the second version, a number of small mistakes found in the paper was ...
openaire +2 more sources
On Shor's r-Algorithm for Problems with Constraints
Introduction. Nonsmooth optimization problems arise in a wide range of applications, including engineering, finance, and deep learning, where activation functions often have discontinuous derivatives, such as ReLU.
Vladimir Norkin, Anton Kozyriev
doaj +1 more source
ObjectivesCurrently, how to plan the safe and efficient movement trajectory of an unmanned surface vehicle (USV) in local waters with multiple known obstacle positions is a research hotspot.MethodsFirst, the obstacle areas are treated with simple and ...
Qingliang LI +4 more
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Novel Neural Network for Dealing with a Kind of Non-smooth Pseudoconvex Optimization Problems [PDF]
The research of optimization problem is favored by researchers.Nonsmooth pseudoconvex optimization problems are a special kind of nonconvex optimization problems,which often appear in machine learning,signal processing,bioinformatics and various ...
YU Xin, LIN Zhi-liang
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