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A Computationally Efficient Feasible Sequential Quadratic Programming Algorithm
 SIAM Journal on Optimization
, 2001
"... . A sequential quadratic programming (SQP) algorithm generating feasible iterates is described and analyzed. What distinguishes this algorithm from previous feasible SQP algorithms proposed by various authors is a reduction in the amount of computation required to generate a new iterate while the pr ..."
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Cited by 58 (0 self)
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. A sequential quadratic programming (SQP) algorithm generating feasible iterates is described and analyzed. What distinguishes this algorithm from previous feasible SQP algorithms proposed by various authors is a reduction in the amount of computation required to generate a new iterate while
A Sequential Quadratic Programming Algorithm with an Additional Equality Constrained Phase
, 2008
"... A sequential quadratic programming (SQP) method is presented that aims to overcome some of the drawbacks of contemporary SQP methods. It avoids the difficulties associated with indefinite quadratic programming subproblems by defining this subproblem to be always convex. The novel feature of the appr ..."
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Cited by 10 (1 self)
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A sequential quadratic programming (SQP) method is presented that aims to overcome some of the drawbacks of contemporary SQP methods. It avoids the difficulties associated with indefinite quadratic programming subproblems by defining this subproblem to be always convex. The novel feature
A sequential quadratic programming algorithm using an incomplete solution of the subproblem
 SIAM Journal of Optimization
, 1995
"... Ary opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do NOT necessarily reflect the views of the above sponsors. ..."
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Cited by 30 (2 self)
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Ary opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do NOT necessarily reflect the views of the above sponsors.
An Improved Sequential Quadratic Programming Algorithm for Solving General Nonlinear Programming Problems ✩
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A SEQUENTIAL QUADRATIC PROGRAMMING ALGORITHM FOR NONCONVEX, NONSMOOTH CONSTRAINED OPTIMIZATION ∗
"... Abstract. We consider optimization problems with objective and constraint functions that may be nonconvex and nonsmooth. Problems of this type arise in important applications, many having solutions at points of nondifferentiability of the problem functions. We present a line search algorithm for sit ..."
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Cited by 13 (2 self)
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for situations when the objective and constraint functions are locally Lipschitz and continuously differentiable on open dense subsets of R n. Our method is based on a sequential quadratic programming (SQP) algorithm that uses an ℓ1 penalty to regularize the constraints. A process of gradient sampling (GS
A feasible trustregion sequential quadratic programming algorithm. Optimization
 SIAM Journal on Optimization
, 2002
"... Abstract. An algorithm for smooth nonlinear constrained optimization problems is described, in which a sequence of feasible iterates is generated by solving a trustregion sequential quadratic programming (SQP) subproblem at each iteration, and perturbing the resulting step to retain feasibility of ..."
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Cited by 4 (1 self)
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Abstract. An algorithm for smooth nonlinear constrained optimization problems is described, in which a sequence of feasible iterates is generated by solving a trustregion sequential quadratic programming (SQP) subproblem at each iteration, and perturbing the resulting step to retain feasibility
A Robust Implementation of a Sequential Quadratic Programming Algorithm with Successive Error Restoration Address:
, 2010
"... We consider sequential quadratic programming (SQP) methods for solving constrained nonlinear programming problems. It is generally believed that SQP methods are sensitive to the accuracy by which partial derivatives are provided. One reason is that differences of gradients of the Lagrangian function ..."
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Cited by 1 (0 self)
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We consider sequential quadratic programming (SQP) methods for solving constrained nonlinear programming problems. It is generally believed that SQP methods are sensitive to the accuracy by which partial derivatives are provided. One reason is that differences of gradients of the Lagrangian
REVISED SEPTEMBER 2003. A FEASIBLE TRUSTREGION SEQUENTIAL QUADRATIC PROGRAMMING ALGORITHM
"... Abstract. An algorithm for smooth nonlinear constrained optimization problems is described, in which a sequence of feasible iterates is generated by solving a trustregion sequential quadratic programming (SQP) subproblem at each iteration, and perturbing the resulting step to retain feasibility of ..."
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Abstract. An algorithm for smooth nonlinear constrained optimization problems is described, in which a sequence of feasible iterates is generated by solving a trustregion sequential quadratic programming (SQP) subproblem at each iteration, and perturbing the resulting step to retain feasibility
NLPQLP: A New Fortran Implementation of a Sequential Quadratic Programming Algorithm for Parallel Computing
"... The Fortran subroutine NLPQLP solves smooth nonlinear programming problems and is an extension ofthe code NLPQL. The new version is specifically tuned to run under distributed systems. A new input parameter l is introduced for the number ofparallel machines, that is the number offunction calls to be ..."
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The Fortran subroutine NLPQLP solves smooth nonlinear programming problems and is an extension ofthe code NLPQL. The new version is specifically tuned to run under distributed systems. A new input parameter l is introduced for the number ofparallel machines, that is the number offunction calls
ABSTRACT Title of Dissertation: A COMPUTATIONALLY EFFICIENT FEASIBLE SEQUENTIAL QUADRATIC PROGRAMMING ALGORITHM
"... ISR develops, applies and teaches advanced methodologies of design and analysis to solve complex, hierarchical, ..."
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ISR develops, applies and teaches advanced methodologies of design and analysis to solve complex, hierarchical,
Results 1  10
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381,772