StructuredOptimization.jl is a high-level modeling language that utilizes a syntax that is very close to the mathematical formulation of an optimization problem.

This user-friendly interface acts as a parser to utilize three different packages:

StructuredOptimization.jl can handle large-scale convex and nonconvex problems with nonsmooth cost functions.

It supports complex variables as well.

To install the package, hit `]`

from the Julia command line to enter the package manager, then

```
pkg> add StructuredOptimization
```

A *least absolute shrinkage and selection operator* (LASSO) can be solved with only few lines of code:

```
julia> using StructuredOptimization
julia> n, m = 100, 10; # define problem size
julia> A, y = randn(m,n), randn(m); # random problem data
julia> x = Variable(n); # initialize optimization variable
julia> λ = 1e-2*norm(A'*y,Inf); # define λ
julia> @minimize ls( A*x - y ) + λ*norm(x, 1); # solve problem
julia> ~x # inspect solution
100-element Array{Float64,1}:
0.0
0.0
0.0
0.440254
0.0
0.0
0.0
[...]
```

See the documentation for more details about the type of problems StructuredOptimization.jl can handle and the demos to check out some examples.

07/05/2016

3 months ago

384 commits