Smoothing approximation to the lower order exact penalty function for inequality constrained optimization [PDF]
Journal of Inequalities and Applications, 2018 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]
Entropy, 2021 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
A unifying theory of exactness of linear penalty functions II: parametric penalty functions [PDF]
Optimization, 2017 In this article we develop a general theory of exact parametric penalty functions for constrained optimization problems. The main advantage of the method of parametric penalty functions is the fact that a parametric penalty function can be both smooth ...
Dolgopolik, M. V.
core +2 more sources
TGN-MCDS: A Temporal Graph Network-Based Algorithm for Cluster-Head Optimization in Large-Scale FANETs [PDF]
SensorsWith the growing deployment of Flying Ad hoc Networks (FANETs) in military and civilian applications, constructing a stable and efficient communication backbone has become a critical challenge.
Xiangrui Fan +3 more
doaj +2 more sources
A new projective exact penalty function for a general constrained optimization
Доповiдi Нацiональної академiї наук України, 2022 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]
Decision Science Letters, 2019 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
doaj +1 more source
Exact penalty functions with multidimensional penalty parameter and adaptive penalty updates [PDF]
Optimization Letters, 2021 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
Кібернетика та комп'ютерні технології, 2023 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
Novel Neural Network for Dealing with a Kind of Non-smooth Pseudoconvex Optimization Problems [PDF]
Jisuanji kexue, 2022 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
doaj +1 more source
Zhongguo Jianchuan Yanjiu, 2021 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
doaj +1 more source