Hi

I am rather new to Julia and I am experimenting with NLopt. I ran the tests on github and they work fine but then I tried my own objective and constraints.

function ps(x,grad)

return x[1]

end

function ps_con(x,grad,w)

f=zeros(2)

f[1]=x[2]^2-1+x[3]

f[2]=-10*x[2]^2+0.1*x[3]

z=-f+w*x[1]

return z

end

I then followed the same procedure followed in the test examples but with a derivative free optimiser.

opt = Opt(:LN_COBYLA, 3)

opt.lower_bounds = [0, -Inf.-Inf]

opt.upper_bounds = [1,Inf,Inf]

opt.xtol_rel = 1e-4

opt.min_objective = ps

opt.inequality_constraint = (x,g) → ps_con(x,g,[1,1])

(minf,minx,ret) = optimize(opt, [1,1,1])

No error occurs but the optimiser does not do anything and exits with either FORCED_STOP or XTOL_REACHED at the first iteration.

Note that calling the objective and constraint functions individually with random inputs does not produce any error.

What am I doing wrong?

Mx