Results 291 to 300 of about 12,262,956 (340)

An exact l1 penalty function method for multi-dimensional first-order PDE constrained control optimization problem

European Journal of Control, 2020
In this paper, we use the exact l1 penalty function method to solve a multi-dimensional first-order PDE constrained control optimization problem. The relationships between the aforesaid problem and its associated penalized problem with the exact l1 ...
Anurag Jayswal, Preeti
semanticscholar   +1 more source

A simple smooth exact penalty function for smooth optimization problem

Journal of Systems Science and Complexity, 2012
Shujun Lian, Liansheng Zhang, Zhang Liansheng   +2 more
exaly   +2 more sources

A New Exact Penalty Function

SIAM Journal on Optimization, 2003
A new approach to exact penalization of a constrained, nonlinear optimization problem is introduced. This is motivated by the desire to deal with the following list of perceived failures of other exact penalty methods: 1. nonsmoothness is avoided; 2. the penalized objective remains bounded below under mild assumptions; 3.
Waltraud Huyer, Arnold Neumaier
openaire   +2 more sources

A new class of exact penalty functions and penalty algorithms

Journal of Global Optimization, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Changyu Wang, Cheng Ma, Jinchuan Zhou
openaire   +1 more source

Convergence of the RMSProp deep learning method with penalty for nonconvex optimization

Neural Networks, 2021
A norm version of the RMSProp algorithm with penalty (termed RMSPropW) is introduced into the deep learning framework and its convergence is addressed both analytically and numerically.
Dongpo Xu, Shengdong Zhang, Huisheng Zhang, D. Mandic   +3 more
semanticscholar   +1 more source

Linearization and Penalty Functions

Cybernetics and Systems Analysis, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

An Objective Penalty Function of Bilevel Programming

Journal of Optimization Theory and Applications, 2011
The authors provide a penalty method for bilevel programming problems according to \[ (\text{BP}):\qquad\min f_1(x,y)\quad\text{s.t. }g_i(x,y)\leq 0,\quad i= 1,\dots, p,\qquad\text{and} \] \[ y\text{ solves the lower level problem }P(x):\min f_2(x,y)\text{ s.t. }h_j(x,y)\leq 0,\;j\in 1,\dots, q, \] where \(f_1,f_2,g_i,h_j: \mathbb{R}^n\times \mathbb{R}^
Zhiqing Meng, Chuangyin Dang, Rui Shen 0001, Ming Jiang   +3 more
openaire   +1 more source

Penalty Functions in a Control Problem

Automation and Remote Control, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

Penalty functions and the knapsack problem

Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence, 2002
This paper reports on a study of the effectiveness of penalty functions used with a standard genetic algorithm to solve a problem with constraints. Twelve different penalty functions were created and tested using a genetic algorithm to solve the zero-one knapsack problem.
openaire   +1 more source

Generalized shrinkage and penalty functions

2013 IEEE Global Conference on Signal and Information Processing, 2013
We extend the proximal mapping property of soft thresholding to a general class of shrinkage mappings. We give an example and demonstrate improved reconstruction performance.
openaire   +1 more source