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An embedded proximal interior point quadratic programming solver, which can solve dense and sparse quadratic programs, described in Schwan, Jiang, Kuhn, and Jones (2023) <doi:10.48550/arXiv.2304.00290>. Combining an infeasible interior point method with the proximal method of multipliers, the algorithm can handle ill-conditioned convex quadratic programming problems without the need for linear independence of the constraints. The solver is written in header only 'C++ 14' leveraging the 'Eigen' library for vectorized linear algebra. For small dense problems, vectorized instructions and cache locality can be exploited more efficiently. Allocation free problem updates and re-solves are also provided.
Version: | 0.2.2 |
Imports: | Matrix, methods, R6, Rcpp |
LinkingTo: | Rcpp, RcppEigen |
Suggests: | knitr, rmarkdown, slam, tinytest |
Published: | 2023-08-14 |
DOI: | 10.32614/CRAN.package.piqp |
Author: | Balasubramanian Narasimhan [aut, cre], Roland Schwan [aut, cph], Yuning Jiang [aut], Daniel Kuhn [aut], Colin N. Jones [aut] |
Maintainer: | Balasubramanian Narasimhan <naras at stanford.edu> |
BugReports: | https://github.com/PREDICT-EPFL/piqp-r/issues |
License: | BSD_2_clause + file LICENSE |
URL: | https://predict-epfl.github.io/piqp-r/ |
NeedsCompilation: | yes |
Citation: | piqp citation info |
Materials: | README |
In views: | Optimization |
CRAN checks: | piqp results |
Reference manual: | piqp.pdf |
Vignettes: |
PIQP Solver Interface |
Package source: | piqp_0.2.2.tar.gz |
Windows binaries: | r-devel: piqp_0.2.2.zip, r-release: piqp_0.2.2.zip, r-oldrel: piqp_0.2.2.zip |
macOS binaries: | r-release (arm64): piqp_0.2.2.tgz, r-oldrel (arm64): piqp_0.2.2.tgz, r-release (x86_64): piqp_0.2.2.tgz, r-oldrel (x86_64): piqp_0.2.2.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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