Novel Interior Point Algorithms for Solving Nonlinear Convex Optimization Problems

This paper proposes three numerical algorithms based on Karmarkar’s interior point technique for solvingnonlinear convex programming problems subject to linear constraints. The first algorithm uses the Karmarkaridea and linearization of the objective function. The second and third algorithms are mod...

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Veröffentlicht in:Advances in Operations Research Jg. 2015; H. 2015; S. 59 - 65
Hauptverfasser: Tahmasebzadeh, Sakineh, Malek, Alaeddin, Navidi, H. R.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cairo, Egypt Hindawi Limiteds 01.01.2015
Hindawi Publishing Corporation
John Wiley & Sons, Inc
Schlagworte:
Algorithms
Analysis
Convex programming
Linear programming
Mathematical optimization
Methods
Operations research
Optimization
Simplex method
United States
ISSN:1687-9147, 1687-9155
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Zusammenfassung:This paper proposes three numerical algorithms based on Karmarkar’s interior point technique for solvingnonlinear convex programming problems subject to linear constraints. The first algorithm uses the Karmarkaridea and linearization of the objective function. The second and third algorithms are modification ofthe first algorithm using the Schrijver and Malek-Naseri approaches, respectively. These three novel schemesare tested against the algorithm of Kebiche-Keraghel-Yassine (KKY). It is shown that these three novel algorithmsare more efficient and converge to the correct optimal solution, while the KKY algorithm fails insome cases. Numerical results are given to illustrate the performance of the proposed algorithms.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1687-9147
1687-9155
DOI:10.1155/2015/487271