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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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
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Abstract 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.
AbstractList 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.
Author Kupferschmid, M.
Ecker, J. G.
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CitedBy_id crossref_primary_10_1007_s40092_017_0230_x
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Cites_doi 10.1007/BF01588967
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SubjectTerms Algorithms
Applied mathematics
Applied sciences
Exact sciences and technology
Libraries
Mathematical programming
Operational research and scientific management
Operational research. Management science
Quadratic programming
Title A Computational Comparison of the Ellipsoid Algorithm with Several Nonlinear Programming Algorithms
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