Quadratic Programming Solver using the 'OSQP' Library

Provides bindings to the 'OSQP' solver, which can solve sparse convex quadratic programming problems with optional equality and inequality constraints.


Provides R-bindings to the OSQP-solver

OSQP is a sparse Quadratic Programming Solver suitable for large problems. It solves problems of the form: $$ argmin(x) 0.5 x'P x + q'x $$

$$s.t.: l_i <= (Ax)_i <= u_i$$

with P Positive semidefinite

OSQP License

The source code of OSQP is provided in the package and it is licensed under Apache 2.0. Copyright (c) 2017 Bartolomeo Stellato, Goran Banjac, Paul Goulart, Stephen Boyd

This product includes software developed at Stanford University and at the University of Oxford.

Please see the file LICENSE and inst/COPYRIGHT for more details.

Example

library(rosqp)
## example, adapted from ?quadprog::solve.QP
Dmat       <- diag(3)
dvec       <- c(0,-5,0)
Amat       <- matrix(c(-4, 2, 0, -3, 1, -2, 0, 0, 1),3,3)
bvec       <- c(-8,2,0)
res = solve_osqp(Dmat, dvec, Amat, bvec)
print(res$x)

News

Reference manual

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install.packages("rosqp")

0.1.0 by Eric Anderson, a year ago


Browse source code at https://github.com/cran/rosqp


Authors: Eric Anderson [aut, cre] , Bartolomeo Stellato [ctb, cph] (OSQP) , Goran Banjac [ctb, cph] (OSQP) , Paul Goulart [ctb, cph] (OSQP) , Stephen Boyd [ctb, cph] (OSQP) , Patrick R. Amestoy [ctb, cph] (SuiteSparse AMD) , Iain S. Duff [ctb, cph] (SuiteSparse AMD) , Timothy A. Davis [ctb, cph] (SuiteSparse LDL , SuiteSparse AMD) , John K. Reid [ctb, cph] (SuiteSparse AMD)


Documentation:   PDF Manual  


Task views:


Apache License 2.0 license


Imports Rcpp, methods, Matrix, R6

Linking to Rcpp


Imported by optweight.


See at CRAN