Erratum to: Nonlinear programming without a penalty function or a filter
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چکیده
منابع مشابه
Erratum to: Nonlinear programming without a penalty function or a filter
This note reports a correction to the results obtained by [2], in which an error was unfortunately discovered during work with D. Robinson. The problem is in the proof of Lemma 3.10 of this reference, where it is claimed that Lemma 6.5.3 of [1] can be invoked to deduce that ρc k ≥ η2, where ρc k is a specific ratio of achieved to predicted reduction is constraint violation and η2 is a constant ...
متن کاملNonlinear programming without a penalty function or a filter
A new method is introduced for solving equality constrained nonlinear optimization problems. This method does not use a penalty function, nor a barrier or a filter, and yet can be proved to be globally convergent to first-order stationary points. It uses different trustregions to cope with the nonlinearities of the objective function and the constraints, and allows inexact SQP steps that do not...
متن کاملNonlinear programming without a penalty function
Abstract. In this paper the solution of nonlinear programming problems by a Sequential Quadratic Programming (SQP) trust-region algorithm is considered. The aim of the present work is to promote global convergence without the need to use a penalty function. Instead, a new concept of a “filter” is introduced which allows a step to be accepted if it reduces either the objective function or the co...
متن کاملA new double trust regions SQP method without a penalty function or a filter∗
A new trust-region SQP method for equality constrained optimization is considered. This method avoids using a penalty function or a filter, and yet can be globally convergent to first-order critical points under some reasonable assumptions. Each SQP step is composed of a normal step and a tangential step for which different trust regions are applied in the spirit of Gould and Toint [Math. Progr...
متن کاملAn Infeasible Bundle Method for Nonsmooth Convex Constrained Optimization without a Penalty Function or a Filter
Global convergence in constrained optimization algorithms has traditionally been enforced by the use of parametrized penalty functions. Recently, the filter strategy has been introduced as an alternative. At least part of the motivation for filter methods consists in avoiding the need for estimating a suitable penalty parameter, which is often a delicate task. In this paper, we demonstrate that...
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ژورنال
عنوان ژورنال: Mathematical Programming
سال: 2011
ISSN: 0025-5610,1436-4646
DOI: 10.1007/s10107-011-0491-x