Results 251 to 260 of about 4,477 (306)

GPU Accelerated Sequential Quadratic Programming

2017 16th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES), 2017
Nonlinear optimization problems arise in all industries. Accelerating optimization solvers is desirable. Efforts have been made to accelerate interior point methods for large scale problems. However, since the interior point algorithm used requires many function evaluations, the acceleration of the algorithm becomes less beneficial.
Xiukun Hu, Craig C. Douglas, Robert Lumley, Mookwon Seo   +3 more
openaire   +1 more source

Projected Sequential Quadratic Programming Methods

SIAM Journal on Optimization, 1996
The author considers the optimization problem Minimize \(f(x)\) subject to \(c(x)=0\), \(a\leq u\leq b\) componentwise, where \(x=(y,u)\in \mathbb{R}^{m+n}\) and \(f:\mathbb{R}^{m+n} \to \mathbb{R}\), \(c: \mathbb{R}^{m+n}\to \mathbb{R}^m\) are sufficiently smooth. Such problems frequently arise in the numerical solution of optimal control problems. In
openaire   +1 more source

Επαναληπτικός τετραγωνικός προγραμματισμός

2013
The aim of this thesis is to study the solution of constrained nonlinear optimization problems using Sequential Quadratic Programming (SQP) method which has proved highly effective in practice. As with most optimization methods, SQP is not a single algorithm but rather a conceptual method from which numerous specific algorithms have evolved.
openaire   +1 more source

SQ2P, Sequential Quadratic Constrained Quadratic Programming

1998
We follow the popular approach for unconstrained minimization, i.e. we develop a local quadratic model at a current approximate minimizer in conjunction with a trust region. We then minimize this local model in order to find the next approximate minimizer.
Serge Kruk, Henry Wolkowicz
openaire   +1 more source

Switching Stepsize Strategies for Sequential Quadratic Programming

Journal of Optimization Theory and Applications, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tzallas-Regas, George, Rustem, Berç
openaire   +2 more sources

Sequential Quadratic Programming for Parameter Identification Problems

IFAC Proceedings Volumes, 1989
Abstract Sequential quadratic programming (SQP) is a technique for nonlinear equality constrained minimization problems, which, from the point of view of local convergence, is equivalent to finding a root of the gradient of the Lagrangian by Newton's method, if the second order sufficient conditions hold. For general, unstructured, finite dimensional
D.M. Hwang, C.T. Kelley
openaire   +1 more source

A Sequential Quadratically Constrained Quadratic Programming Method of Feasible Directions

Applied Mathematics and Optimization, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jian, Jin-bao, Hu, Qing-jie, Tang, Chun-ming, Zheng, Hai-yan   +3 more
openaire   +1 more source

Hydropower Optimization Via Sequential Quadratic Programming

Journal of Water Resources Planning and Management, 1989
Optimal allocation of powerplant releases during peak demand periods carries an economic advantage in the operation of hydropower systems interconnected to large electrical networks. This paper presents an alternative formulation for determining release strategies when the objective is not maximizing total hydroelectric generation per se, but rather ...
Gustavo E. Díaz, Darrell G. Fontane
openaire   +1 more source

Sequential Quadratic Programming Methods

2011
In his 1963 PhD thesis, Wilson proposed the first sequential quadratic programming (SQP) method for the solution of constrained nonlinear optimization problems. In the intervening 48 years, SQP methods have evolved into a powerful and effective class of methods for a wide range of optimization problems. We review some of the most prominent developments
Philip E. Gill, Elizabeth Wong
openaire   +1 more source

VAR compensation by sequential quadratic programming

IEEE Transactions on Power Systems, 2003
This paper presents an application of the sequential quadratic programming method to find the optimal sizing of shunt capacitors and/or passive filters for maximizing the net present value resulting from energy-loss reduction while taking investment cost into account and complying with the IEEE-519 standard.
I. Perez Abril, J. Gonzelez Quintero
openaire   +1 more source