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LARGESCALE LINEARLY CONSTRAINED OPTIMIZATION
, 1978
"... An algorithm for solving largescale nonlinear ' programs with linear constraints is presented. The method combines efficient sparsematrix techniques as in the revised simplex method with stable quasiNewton methods for handling the nonlinearities. A generalpurpose production code (MINOS) is descr ..."
Abstract

Cited by 75 (11 self)
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An algorithm for solving largescale nonlinear ' programs with linear constraints is presented. The method combines efficient sparsematrix techniques as in the revised simplex method with stable quasiNewton methods for handling the nonlinearities. A generalpurpose production code (MINOS) is described, along with computational experience on a wide variety of problems.
Newton methods for largescale linear inequalityconstrained minimization
 SIAM Journal on Optimization
, 1997
"... Abstract. Newton methods of the linesearch type for largescale minimization subject to linear inequality constraints are discussed. The purpose of the paper is twofold: (i) to give an active–settype method with the ability to delete multiple constraints simultaneously and (ii) to give a relatively ..."
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Cited by 7 (0 self)
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Abstract. Newton methods of the linesearch type for largescale minimization subject to linear inequality constraints are discussed. The purpose of the paper is twofold: (i) to give an active–settype method with the ability to delete multiple constraints simultaneously and (ii) to give a relatively short general convergence proof for such a method. It is also discussed how multiple constraints can be added simultaneously. The approach is an extension of a previous work by the same authors for equalityconstrained problems. It is shown how the search directions can be computed without the need to compute the reduced Hessian of the objective function. The convergence analysis states that every limit point of a sequence of iterates satisfies the secondorder necessary optimality conditions. Key words. linear inequalityconstrained minimization, negative curvature, modified Newton method, symmetric indefinite factorization, largescale minimization, linesearch method
NorthHolland Publishing Company MATRIX FACTOR1ZATIONS IN OPTIMIZATION OF NON LINEAR FUNCTIONS SUBJECT TO LINEAR CONSTRAINTS*
, 1974
"... Several ways of implementing methods for solving nonlinear optimization problems involving linear inequality and equality constraints using numerically stable matrix factorizations are described. The methods considered all follow an active constraint set approach and include quadratic programming, v ..."
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Several ways of implementing methods for solving nonlinear optimization problems involving linear inequality and equality constraints using numerically stable matrix factorizations are described. The methods considered all follow an active constraint set approach and include quadratic programming, variable metric, and modified Newton methods. 1.