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SNOPT: An SQP Algorithm For Large-Scale Constrained Optimization

by Philip E. Gill, Walter Murray, Michael A. Saunders , 2002
"... Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints. Here we consider problems with general inequality constraints (linear and nonlinear). We assume that first deriv ..."
Abstract - Cited by 597 (24 self) - Add to MetaCart
Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints. Here we consider problems with general inequality constraints (linear and nonlinear). We assume that first

Using a Filter-Based SQP Algorithm in a Parallel Environment

by Gerhard Venter, Garret N. Vanderplaats
"... A parallel, filter-based, sequential quadratic programming (SQP) algorithm is implemented and ..."
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A parallel, filter-based, sequential quadratic programming (SQP) algorithm is implemented and

On the Global Convergence of a Filter-SQP Algorithm

by Roger Fletcher, Sven Leyffer, Philippe L. Toint , 2000
"... A mechanism for proving global convergence in filter-type methods for nonlinear programming is described. Such methods are characterized by their use of the dominance concept of multiobjective optimization, instead of a penalty parameter whose adjustment can be problematic. The main point of interes ..."
Abstract - Cited by 46 (8 self) - Add to MetaCart
of interest is to demonstrate how convergence for NLP can be induced without forcing sucient descent in a penalty-type merit function. The proof relates to a prototypical algorithm, within which is allowed a range of specific algorithm choices associated with the Hessian matrix representation, updating

Analysis of Inexact Trust-Region SQP Algorithms

by Matthias Heinkenschloss, Luís N. Vicente - RICE UNIVERSITY, DEPARTMENT OF , 2000
"... In this paper we extend the design of a class of composite-step trust-region SQP methods and their global convergence analysis to allow inexact problem information. The inexact problem information can result from iterative linear systems solves within the trust-region SQP method or from approximatio ..."
Abstract - Cited by 26 (2 self) - Add to MetaCart
In this paper we extend the design of a class of composite-step trust-region SQP methods and their global convergence analysis to allow inexact problem information. The inexact problem information can result from iterative linear systems solves within the trust-region SQP method or from

On the solution to the subproblems of a globally convergent SQP algorithm for nonlinear programming *

by F A M Gomes , S A Santos , R C A Thomé
"... Abstract This work introduces a bound-constrained-based strategy for dealing with the quadratic subproblems of the sequential quadratic programming (SQP) algorithm proposed by ..."
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Abstract This work introduces a bound-constrained-based strategy for dealing with the quadratic subproblems of the sequential quadratic programming (SQP) algorithm proposed by

An efficient feasible SQP algorithm for inequality constrained optimization

by Zhibin Zhu , Jinbao Jian , 2009
"... ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
Abstract not found

A Truncated SQP Algorithm for Large Scale Nonlinear Programming Problems

by Paul T. Boggs, Jon W. Tolle, Anthony J. Kearsley - Advances in Optimization and Numerical Analysis: Proceedings of the Sixth Workshop on Optimization and Numerical Analysis
"... We consider the inequality constrained nonlinear programming problem and an SQP algorithm for its solution. We are primarily concerned with two aspects of the general procedure, namely, the approximate solution of the quadratic program, and the need for an appropriate merit function. We first descri ..."
Abstract - Cited by 6 (3 self) - Add to MetaCart
We consider the inequality constrained nonlinear programming problem and an SQP algorithm for its solution. We are primarily concerned with two aspects of the general procedure, namely, the approximate solution of the quadratic program, and the need for an appropriate merit function. We first

Analysis of Inexact Trust-Region Interior-Point SQP Algorithms

by Matthias Heinkenschloss, Luís N. Vicente , 1995
"... In this paper we analyze inexact trust-region interior-point (TRIP) sequential quadratic programming (SQP) algorithms for the solution of optimization problems with nonlinear equality constraints and simple bound constraints on some of the variables. Such problems arise in many engineering applicati ..."
Abstract - Cited by 11 (7 self) - Add to MetaCart
In this paper we analyze inexact trust-region interior-point (TRIP) sequential quadratic programming (SQP) algorithms for the solution of optimization problems with nonlinear equality constraints and simple bound constraints on some of the variables. Such problems arise in many engineering

A trust region SQP algorithm for mixed-integer nonlinear programming

by Oliver Exler , Klaus Schittkowski , Klaus Schittkowski - ANNALS of the ORADEA UNIVERSITY. Fascicle of Management and Technological Engineering, Volume X (XX , 2007
"... Abstract We propose a modified sequential quadratic programming (SQP) method for solving mixed-integer nonlinear programming problems. Under the assumption that integer variables have a smooth influence on the model functions, i.e., that function values do not change drastically when in-or decremen ..."
Abstract - Cited by 11 (1 self) - Add to MetaCart
Abstract We propose a modified sequential quadratic programming (SQP) method for solving mixed-integer nonlinear programming problems. Under the assumption that integer variables have a smooth influence on the model functions, i.e., that function values do not change drastically when in

On the Convergence of a Trust Region SQP Algorithm for Nonlinearly Constrained Optimization Problems

by Paul T. Boggs, Jon W. Tolle, Anthony J. Kearsley , 1995
"... In (Boggs, Tolle and Kearsley 1994b) the authors introduced an effective algorithm for general large scale nonlinear programming problems. In this paper we describe the theoretical foundation for this method. The algorithm is based on a trust region, sequential quadratic programming (SQP) technique ..."
Abstract - Cited by 2 (2 self) - Add to MetaCart
In (Boggs, Tolle and Kearsley 1994b) the authors introduced an effective algorithm for general large scale nonlinear programming problems. In this paper we describe the theoretical foundation for this method. The algorithm is based on a trust region, sequential quadratic programming (SQP) technique
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