A Computational Comparison of the Ellipsoid Algorithm with Several Nonlinear Programming Algorithms

A computational comparison of several general purpose nonlinear programming algorithms is presented. This study was motivated by the preliminary results in [12] which show that the recently developed ellipsoid algorithm is competitive with a widely used augmented Lagrangian algorithm. To provide a b...

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Bibliographic Details
Published in:SIAM journal on control and optimization Vol. 23; no. 5; pp. 657 - 674
Main Authors: Ecker, J. G., Kupferschmid, M.
Format: Journal Article
Language:English
Published: Philadelphia, PA Society for Industrial and Applied Mathematics 01.09.1985
Subjects:
Algorithms
Applied mathematics
Applied sciences
Exact sciences and technology
Libraries
Mathematical programming
Operational research and scientific management
Operational research. Management science
Quadratic programming
Algorithm
Non linear programming
Mathematical programming
ISSN:0363-0129, 1095-7138
Online Access:Get full text
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Summary:A computational comparison of several general purpose nonlinear programming algorithms is presented. This study was motivated by the preliminary results in [12] which show that the recently developed ellipsoid algorithm is competitive with a widely used augmented Lagrangian algorithm. To provide a better perspective on the value of ellipsoid algorithms in nonlinear programming, the present study includes some of the most highly regarded nonlinear programming algorithms and is a much more comprehensive study than [12]. The algorithms considered here are chosen from four distinct classes and 50 well-known test problems are used. The algorithms used represent augmented Lagrangian, ellipsoid, generalized reduced gradient, and iterative quadratic programming methods. Results regarding robustness and relative efficiency are presented.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0363-0129
1095-7138
DOI:10.1137/0323042