**Nonlinear programming without a penalty function.** / Fletcher, Roger; Leyffer, Sven.

Research output: Contribution to journal › Article

Fletcher, R & Leyffer, S 2002, 'Nonlinear programming without a penalty function' *Mathematical Programming*, vol 91, no. 2, pp. 239-269. DOI: 10.1007/s101070100244

Fletcher, R., & Leyffer, S. (2002). Nonlinear programming without a penalty function. *Mathematical Programming*, *91*(2), 239-269. DOI: 10.1007/s101070100244

Fletcher R, Leyffer S. Nonlinear programming without a penalty function. Mathematical Programming. 2002;91(2):239-269. Available from, DOI: 10.1007/s101070100244

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title = "Nonlinear programming without a penalty function",

keywords = "Nonlinear programming, SQP, Filter, Penalty function",

author = "Roger Fletcher and Sven Leyffer",

note = "dc.publisher: Springer",

year = "2002",

doi = "10.1007/s101070100244",

volume = "91",

pages = "239--269",

journal = "Mathematical Programming",

issn = "0025-5610",

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TY - JOUR

T1 - Nonlinear programming without a penalty function

AU - Fletcher,Roger

AU - Leyffer,Sven

N1 - dc.publisher: Springer

PY - 2002

Y1 - 2002

N2 - 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.

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

T2 - Mathematical Programming

JF - Mathematical Programming

SN - 0025-5610

IS - 2

ER -