Here is a very stripped down toy example that is roughly equivalent to my real problem (without any constraints):
using JuMP using Ipopt N = 54 r = rand(N) R = rand() model = Model(Ipopt.Optimizer) @variable(model, s[1:N]) @NLobjective( model, Min, sum(abs((r[i]/s[i]) - R) for i in 1:N) ) JuMP.optimize!(model)
R is a “target ratio” and I would like to minimize the sum of the absolute differences between each of 54 different ratios and the target ratio by modifying the denominators
s. In my actual problem, r is a 54 x 4 matrix, there are 4 target ratios, and I have constraints that each value of
s can take, as well as a constraint on the sum of
s (and I’m trying to minimize the sum of the sums of the absolute differences). However, with the real problem and with this stripped down version, I get the following error:
Also, if I call
objective_function(model) it returns 0…Any ideas as to how I can formulate this problem?