Nonlinear programming without a penalty function

Roger Fletcher; Sven Leyffer

doi:10.1007/s101070100244

Nonlinear programming without a penalty function

Roger Fletcher
, Sven Leyffer

Research output: Contribution to journal › Article › peer-review

697 Citations (Scopus)

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 constraint violation function. Numerical tests on a wide range of test problems are very encouraging and the new algorithm compares favourably with LANCELOT and an implementation of Sl1QP.

Original language	English
Pages (from-to)	239-269
Number of pages	31
Journal	Mathematical Programming
Volume	91
Issue number	2
DOIs	https://doi.org/10.1007/s101070100244
Publication status	Published - 2002

Keywords

Nonlinear programming
SQP
Filter
Penalty function

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10.1007/s101070100244

Cite this

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title = "Nonlinear 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 constraint violation function. Numerical tests on a wide range of test problems are very encouraging and the new algorithm compares favourably with LANCELOT and an implementation of Sl1QP.",

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AB - 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 constraint violation function. Numerical tests on a wide range of test problems are very encouraging and the new algorithm compares favourably with LANCELOT and an implementation of Sl1QP.

KW - Nonlinear programming

KW - SQP

KW - Filter

KW - Penalty function

U2 - 10.1007/s101070100244

DO - 10.1007/s101070100244

M3 - Article

VL - 91

SP - 239

EP - 269

JO - Mathematical Programming

JF - Mathematical Programming

IS - 2

ER -

Nonlinear programming without a penalty function

Abstract

Keywords

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