Hi there,
Sorry about the formatting on a previous version of the post. I am new to Julia and doing research in demand modelling. And I apologize if this is too basic. I am thinking to move my code from Rcpp to Julia to solve MPEC, mainly a optimization problem with lots of non-convex constraints (normally 100k+). I’ve heard that JuMP is a great choice due to its AD tools and efficiency. However, I encountered some difficulties here when coding my nonlinear constraint. I coded a function model_constraint whose output is a n_constraint by 1 column vector that will be the Right hand side of my nonlinear constraints. The dimension could be 20,50 and depends on the data so I cannot pin it down before hand. I know that from the other thread I could workaround the requirement that nonlinear objective functions only take scalar input by using the trick
function GMM_obj(ita...)
ita_vec = collect(ita)
....
end
And while setting objective, do
JuMP.setNLobjective(mod, :Min, Expr(:call, :GMM_obj, [x[i] for i=1:n_x]…))
I tried to do similar things when the NL constraints defined by the following user-defined functions have variable length of input and output:
function model_constraint(xlist...)
x = collect(xlist)
...
end
My thought was to store the vector output of the nonlinear function into a NLexpression and use a for loop to set the constraint 1 by 1 as below
JuMP.register(mod, :model_constraint, n_x, model_constraint, autodiff=true)
@expression(mod, GMM_constraint_LHS, zeros(n_constraint,1))
@NLexpression(mod, GMM_constraint_RHS, Expr(:call, :model_constraint, [x[i] for i=1:n_x]...))
for j in 1:n_constraint
@NLconstraints(mod, GMM_constraint_LHS[j] == GMM_constraint_RHS[j])
end
But the line with NLexpression has error:
Unrecognized function “Expr” used in nonlinear expression.
in error at base\error.jl:21
I know the caveat for large number of input dimension or constraints but the problem here is not really about high dimension but the variable number of constraints. I have n nonlinear constraints and I cannot handcode them and have to rely on a loop to specify them if JuMP doesn’t support vector NL constraints. Is there any elegant way to do it? Thanks!