README.Rmd

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# CVXR <img src="man/figures/logo.png" width="100" align="right" />
[![R-CMD-check](https://github.com/cvxgrp/CVXR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/cvxgrp/CVXR/actions/workflows/R-CMD-check.yaml)
[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/CVXR)](https://cran.r-project.org/package=CVXR)
[![](https://cranlogs.r-pkg.org/badges/CVXR)](https://CRAN.R-project.org/package=CVXR)

CVXR provides an object-oriented modeling language for convex
optimization, similar to `CVX`, `CVXPY`, `YALMIP`, and `Convex.jl`. It
allows the user to formulate convex optimization problems in a natural
mathematical syntax rather than the restrictive standard form required
by most solvers. The user specifies an objective and set of
constraints by combining constants, variables, and parameters using a
library of functions with known mathematical properties. `CVXR` then
applies signed [disciplined convex programming
(DCP)](https://web.stanford.edu/~boyd/papers/pdf/disc_cvx_prog.pdf) to
verify the problem’s convexity. Once verified, the problem is
converted into standard conic form using graph implementations and
passed to a cone solver such as
[ECOS](https://github.com/embotech/ecos) or
[SCS](https://github.com/cvxgrp/scs).

CVXR includes several open source solvers in addition to the default
OSQP, ECOS and SCS. Recent (1.x+) versions also include support for
commercial solvers such as [MOSEK](https://www.mosek.com),
[GUROBI](https://www.gurobi.com) and
[CPLEX](https://www.ibm.com/products/ilog-cplex-optimization-studio/cplex-optimizer).

For details and examples, we refer you to [Fu, Narasimhan,
Boyd](https://dx.doi.org/10.18637/jss.v094.i14) (2020). If you use
CVXR in your work, please cite this reference. (The R command
`citation("CVXR", bibtex = TRUE)` will also give you a
bibtex-formatted entry.)

## Installation

This package is now released on CRAN, so you can install the current
released version as you would any other package for R, version 3.4
and higher. (`CVXR` is known to work with earlier versions of R too,
but we don't check our releases against older versions of R.)

```{r, eval = FALSE}
install.packages('CVXR', repos = "https://CRAN.R-project.org")
```

Development versions can be installed from the Github repository
assuming you have the development tools
for R available, including the C compilers etc. Execute:

```{r, eval = FALSE}
library(devtools)
install_github("cvxgrp/CVXR")
```

## Tutorial

A number of tutorial examples are available on the [CVXR
website](https://cvxr.rbind.io) along with links to our useR! 2019
short-course.