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SNOPT: An SQP Algorithm For LargeScale Constrained Optimization
, 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 ..."
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Cited by 582 (23 self)
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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 FilterBased SQP Algorithm in a Parallel Environment
"... A parallel, filterbased, sequential quadratic programming (SQP) algorithm is implemented and ..."
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A parallel, filterbased, sequential quadratic programming (SQP) algorithm is implemented and
On the Global Convergence of a FilterSQP Algorithm
, 2000
"... A mechanism for proving global convergence in filtertype 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 ..."
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Cited by 43 (8 self)
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of interest is to demonstrate how convergence for NLP can be induced without forcing sucient descent in a penaltytype 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 TrustRegion SQP Algorithms
 RICE UNIVERSITY, DEPARTMENT OF
, 2000
"... In this paper we extend the design of a class of compositestep trustregion 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 trustregion SQP method or from approximatio ..."
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Cited by 26 (2 self)
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In this paper we extend the design of a class of compositestep trustregion 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 trustregion SQP method or from
A Truncated SQP Algorithm for Large Scale Nonlinear Programming Problems
 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 ..."
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Cited by 5 (3 self)
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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 TrustRegion InteriorPoint SQP Algorithms
, 1995
"... In this paper we analyze inexact trustregion interiorpoint (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 ..."
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Cited by 11 (7 self)
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In this paper we analyze inexact trustregion interiorpoint (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
Comparative results of DE variants and a SQP algorithm to maximize the dexterity of
"... an omnidirectional wheeled mobile robot ..."
On the Convergence of a Trust Region SQP Algorithm for Nonlinearly Constrained Optimization Problems
, 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 ..."
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Cited by 2 (2 self)
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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
The SQPAlgorithm for a Class of Weakly Singular Optimal Control Problems
, 1997
"... this paper is the derivation of optimality systems and the analysis of the sequential quadratic programming (SQP)method for a class of optimal control problems which are weakly singular in a sense to be described shortly. We consider (P) min f(x) + g(u) ..."
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this paper is the derivation of optimality systems and the analysis of the sequential quadratic programming (SQP)method for a class of optimal control problems which are weakly singular in a sense to be described shortly. We consider (P) min f(x) + g(u)
A truncated SQP algorithm for solving nonconvex equality constrained optimization problems
, 2001
"... An algorithm for solving equality constrained optimization problems is proposed. It can deal with nonconvex functions and uses a truncated conjugate algorithm for detecting nonconvexity. The algorithm ensures convergence from remote starting point by using linesearch. Numerical experiments are repo ..."
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An algorithm for solving equality constrained optimization problems is proposed. It can deal with nonconvex functions and uses a truncated conjugate algorithm for detecting nonconvexity. The algorithm ensures convergence from remote starting point by using linesearch. Numerical experiments
Results 1  10
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5,982