Nonlinear Optimization with Many Constraints + Autodifferentiation: Which Julia Solution?

[gdalle]

@SebKrantz

This example works, but it seems it is hard-coding the values of auxdata in the constraints.

I think you could directly do

@constraint(model, auxdata * x[1:n] .<= 0)

to avoid closures over global variables.

@SebKrantz

My real constraints function is significantly more complex

One of the things I like about JuMP is that it lets you add tons of small constraints instead of a single big one. So maybe if your function is too complex you can decompose it?

@SebKrantz

there this gives an error.

What kind of error? Can you give the stack trace and the line where it occurs? It is hard to help you with this level of detail.

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@SebKrantz

In any case, not really concinved that the interface is suitable to put large scale tasks into production.

I have personally helped put large tasks into production using JuMP, so I respectfully disagree Happy to help you debug yours as best I can though!