I’m trying to solve this optimization problem:
But i’m not really sure about how to write down that objective function, I tried doing this:
using JuMP using Ipopt model = Model(Ipopt.Optimizer) set_attribute(model, "print_level",4) set_optimizer_attribute(model, "max_iter",20000) set_attribute(model, "print_timing_statistics","yes") n = 32 #number of charges @variables(model, begin -1 ≤ x[1:n] ≤ 1 -1 ≤ y[1:n] ≤ 1 -1 ≤ z[1:n] ≤ 1 end) @NLobjective(model, Min, sum(sum(1/sqrt((x[i] - x[j])^2 + (y[i] - [j])^2 + (z[i] - z[j])^2) for j=i+1:n) for i=1:n-1 )) optimize!(model)
It’s slightly different since I’m not using spherical coordinates, but what really matters is how to set the objective function with the double summatory.
This will be used for generating 32 equidistant points over an unitary sphere surface.
How do you all recommend me to solve this optimization problem with JuMP ?