From d98c8acb470ce41b7d6f0f6fd583b9fd0afb3fd0 Mon Sep 17 00:00:00 2001
From: Oscar Dowson <odow@users.noreply.github.com>
Date: Thu, 18 May 2023 12:39:29 +1200
Subject: [PATCH] Update README.md for JuMP documentation

---
 README.md | 38 ++++++++++++++++++++++++++++++--------
 1 file changed, 30 insertions(+), 8 deletions(-)

diff --git a/README.md b/README.md
index c0b56ce..8835ad5 100644
--- a/README.md
+++ b/README.md
@@ -1,19 +1,41 @@
 # OSQP.jl
 
-[![Build Status](https://github.com/oxfordcontrol/OSQP.jl/workflows/CI/badge.svg)](https://github.com/oxfordcontrol/OSQP.jl/actions) 
-[![codecov.io](http://codecov.io/github/oxfordcontrol/OSQP.jl/coverage.svg?branch=master)](http://codecov.io/github/oxfordcontrol/OSQP.jl?branch=master)
+[![Build Status](https://github.com/osqp/OSQP.jl/workflows/CI/badge.svg)](https://github.com/osqp/OSQP.jl/actions) 
+[![codecov.io](http://codecov.io/github/osqp/OSQP.jl/coverage.svg?branch=master)](http://codecov.io/github/osqp/OSQP.jl?branch=master)
 
-Julia wrapper for [OSQP](https://osqp.org/): the Operator Splitting QP Solver.
+[OSQP.jl](https://github.com/osqp/OSQP.jl) is a Julia wrapper for
+[OSQP](https://osqp.org/): the Operator Splitting QP Solver.
 
-The OSQP (Operator Splitting Quadratic Program) solver is a numerical optimization package for solving problems in the form
+## License
+
+OSQP.jl is licensed under the [Apache-2.0 license](https://github.com/osqp/OSQP.jl/blob/master/LICENSE.md).
+
+The upstream solver, [osqp/osqp](https://github.com/osqp/osqp) is also licensed
+under the [Apache-2.0 license](https://github.com/osqp/osqp/blob/master/LICENSE).
+
+## Installation
+
+Install OSQP.jl using the Julia package manager
+
+```julia
+import Pkg
+Pkg.add("OSQP")
+```
+
+## Problem class
+
+The OSQP (Operator Splitting Quadratic Program) solver is a numerical
+optimization package for solving problems in the form
 ```
 minimize        0.5 x' P x + q' x
 
 subject to      l <= A x <= u
 ```
-
-where `x in R^n` is the optimization variable. The objective function is defined by a positive semidefinite matrix `P in S^n_+` and vector `q in R^n`. The linear constraints are defined by matrix `A in R^{m x n}` and vectors `l in R^m U {-inf}^m`, `u in R^m U {+inf}^m`.
-
+where `x in R^n` is the optimization variable. The objective function is defined
+by a positive semidefinite matrix `P in S^n_+` and vector `q in R^n`. The linear
+constraints are defined by matrix `A in R^{m x n}` and vectors
+`l in R^m U {-inf}^m`, `u in R^m U {+inf}^m`.
 
 ## Documentation
-The interface is documented [here](https://osqp.org/).
+
+Detailed documentation is available at [https://osqp.org/](https://osqp.org/).