Interior-point methods for nonconvex nonlinear programming: Jamming and numerical testing

Hande Y. Benson; David F. Shanno; Robert J. Vanderbei

doi:10.1007/s10107-003-0418-2

Interior-point methods for nonconvex nonlinear programming: Jamming and numerical testing

Hande Y. Benson, David F. Shanno, Robert J. Vanderbei

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

34 Scopus citations

Abstract

The paper considers an example of Wächter and Biegler which is shown to converge to a nonstationary point for the standard primal-dual interior-point method for nonlinear programming. The reason for this failure is analyzed and a heuristic resolution is discussed. The paper then characterizes the performance of LOQO, a line-search interior-point code, on a large test set of nonlinear programming problems. Specific types of problems which can cause LOQO to fail are identified.

Original language	English (US)
Pages (from-to)	35-48
Number of pages	14
Journal	Mathematical Programming
Volume	99
Issue number	1
DOIs	https://doi.org/10.1007/s10107-003-0418-2
State	Published - Jan 2004

All Science Journal Classification (ASJC) codes

Software
General Mathematics

Keywords

Interior-point methods
Jamming
Nonconvex optimization
Nonlinear programming

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10.1007/s10107-003-0418-2

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abstract = "The paper considers an example of W{\"a}chter and Biegler which is shown to converge to a nonstationary point for the standard primal-dual interior-point method for nonlinear programming. The reason for this failure is analyzed and a heuristic resolution is discussed. The paper then characterizes the performance of LOQO, a line-search interior-point code, on a large test set of nonlinear programming problems. Specific types of problems which can cause LOQO to fail are identified.",

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AB - The paper considers an example of Wächter and Biegler which is shown to converge to a nonstationary point for the standard primal-dual interior-point method for nonlinear programming. The reason for this failure is analyzed and a heuristic resolution is discussed. The paper then characterizes the performance of LOQO, a line-search interior-point code, on a large test set of nonlinear programming problems. Specific types of problems which can cause LOQO to fail are identified.

KW - Interior-point methods

KW - Jamming

KW - Nonconvex optimization

KW - Nonlinear programming

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JF - Mathematical Programming

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Interior-point methods for nonconvex nonlinear programming: Jamming and numerical testing

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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