LOQO
LOQO: An interior point code for quadratic programming. This paper describes a software package, called LOQO, which implements a primal-dual interior-point method for general nonlinear programming. We focus in this paper mainly on the algorithm as it applies to linear and quadratic programming with only brief mention of the extensions to convex and general nonlinear programming, since a detailed paper describing these extensions was published recently elsewhere. In particular, we emphasize the importance of establishing and maintaining symmetric quasidefiniteness of the reduced KKT system. We show that the industry standard MPS format can be nicely formulated in such a way to provide quasidefiniteness. Computational results are included for a variety of linear and quadratic programming problems.
Keywords for this software
References in zbMATH (referenced in 201 articles , 1 standard article )
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Sorted by year (- Vanderbei, Robert J.: Linear programming. Foundations and extensions (2020)
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- Gould, Nicholas I. M.; Robinson, Daniel P.: A dual gradient-projection method for large-scale strictly convex quadratic problems (2017)
- Le Thi, Hoai An; Pham Dinh, Tao: Difference of convex functions algorithms (DCA) for image restoration via a Markov random field model (2017)
- Wan, Wei; Biegler, Lorenz T.: Structured regularization for barrier NLP solvers (2017)
- Yang, Yaguang: CurveLP-A MATLAB implementation of an infeasible interior-point algorithm for linear programming (2017)
- Zhu, Zhichuan; Yu, Bo: Globally convergent homotopy algorithm for solving the KKT systems to the principal-agent bilevel programming (2017)
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- Vanderbei, Robert; Lin, Kevin; Liu, Han; Wang, Lie: Revisiting compressed sensing: exploiting the efficiency of simplex and sparsification methods (2016)