Nonconvex.jl
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Toolbox for gradient-based and derivative-free non-convex constrained optimization with continuous and/or discrete variables.
Not sure if this is the right spot, sorry if not! I would like to state (in my case for an optimization problem I would like to solve with ipopt)...
Is there an option in Nonconvex.jl to output the results every 20 iterations? Kind of like a callback function?
Given that #130 was resolved I wanted to checkout the performance of Zygote for AC-OPF (i.e. the [rosetta-opf example](https://github.com/lanl-ansi/rosetta-opf/blob/main/nonconvex.jl#L228-L233)). I ran into a couple issues you may have some ideas...
https://github.com/thowell/CALIPSO.jl
@ccoffrin and I are interested in evaluating Nonconvex.jl to test out some different solvers and AD systems. However, we're stymied by conversions from JuMP to Nonconvex: ```Julia julia> using JuMP...
```Julia julia> using JuMP julia> import Nonconvex julia> Nonconvex.@load Ipopt [ Info: Attempting to load the package NonconvexIpopt. [ Info: Loading succesful. julia> model = JuMP.Model(); julia> @variable(model, x >=...