A robust SQP method based on a smoothing lower order penalty function

K. W. Meng; S. J. Li; Xiaoqi Yang

doi:10.1080/02331930701761193

A robust SQP method based on a smoothing lower order penalty function

K. W. Meng
, S. J. Li
, Xiaoqi Yang

Research output: Journal article publication › Journal article › Academic research › peer-review

10 Citations (Scopus)

Abstract

Based on a smoothing approximation of a lower order penalty function and following Facchinei's method of dealing with the inconsistency of subproblems in SQP methods, we present a new robust SQP algorithm for solving a nonlinear constrained optimization problem. The proposed algorithm incorporates automatic adjustment rules for the choice of parameters. Under a new regularity condition at infeasible points, the algorithm is proved to be globally convergent.

Original language	English
Pages (from-to)	23-38
Number of pages	16
Journal	Optimization
Volume	58
Issue number	1
DOIs	https://doi.org/10.1080/02331930701761193
Publication status	Published - 1 Jan 2009

Keywords

Nonlinear programming
Regularity condition
SQP method

ASJC Scopus subject areas

Applied Mathematics
Control and Optimization
Management Science and Operations Research

More information

10.1080/02331930701761193

Cite this

@article{b5176a7b74fa40fea704f9d41b1a994d,

title = "A robust SQP method based on a smoothing lower order penalty function",

abstract = "Based on a smoothing approximation of a lower order penalty function and following Facchinei's method of dealing with the inconsistency of subproblems in SQP methods, we present a new robust SQP algorithm for solving a nonlinear constrained optimization problem. The proposed algorithm incorporates automatic adjustment rules for the choice of parameters. Under a new regularity condition at infeasible points, the algorithm is proved to be globally convergent.",

keywords = "Nonlinear programming, Regularity condition, SQP method",

author = "Meng, \{K. W.\} and Li, \{S. J.\} and Xiaoqi Yang",

year = "2009",

month = jan,

day = "1",

doi = "10.1080/02331930701761193",

language = "English",

volume = "58",

pages = "23--38",

journal = "Optimization",

issn = "0233-1934",

publisher = "Taylor and Francis Ltd.",

number = "1",

}

TY - JOUR

T1 - A robust SQP method based on a smoothing lower order penalty function

AU - Meng, K. W.

AU - Li, S. J.

AU - Yang, Xiaoqi

PY - 2009/1/1

Y1 - 2009/1/1

N2 - Based on a smoothing approximation of a lower order penalty function and following Facchinei's method of dealing with the inconsistency of subproblems in SQP methods, we present a new robust SQP algorithm for solving a nonlinear constrained optimization problem. The proposed algorithm incorporates automatic adjustment rules for the choice of parameters. Under a new regularity condition at infeasible points, the algorithm is proved to be globally convergent.

AB - Based on a smoothing approximation of a lower order penalty function and following Facchinei's method of dealing with the inconsistency of subproblems in SQP methods, we present a new robust SQP algorithm for solving a nonlinear constrained optimization problem. The proposed algorithm incorporates automatic adjustment rules for the choice of parameters. Under a new regularity condition at infeasible points, the algorithm is proved to be globally convergent.

KW - Nonlinear programming

KW - Regularity condition

KW - SQP method

UR - https://www.scopus.com/pages/publications/61449261166

U2 - 10.1080/02331930701761193

DO - 10.1080/02331930701761193

M3 - Journal article

SN - 0233-1934

VL - 58

SP - 23

EP - 38

JO - Optimization

JF - Optimization

IS - 1

ER -

A robust SQP method based on a smoothing lower order penalty function

Abstract

Keywords

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this