SLSQP in NLopt.jl 1.0.2 throws error: bug: more than iter SQP iterations

[thorek1]

I understand 1.0.1 => 1.0.2 brought changes to the error handling.

this is inconvenient in the case of SLSQP because it (now) throws an error when maxeval is reached and the optimisation failed. for my purposes it would be useful to have access to the return values even if the optimisation failed/errored. in other words, not throw an error and hand over return values

[stevengj]

That's weird, it's supposed to never reach that check, since we check the evaluation count elsewhere.

[thorek1]

I linked the wrong line. now corrected to L2585

I don't fully grasp the flow of the script (yet) but I can confirm that he throws: bug: more than iter SQP iterations

[odow]

Do you have a reproducible example?

[mzaffalon]

I get the same error. Here is a MWE:

using NLopt

ξ = [-1.0, -0.8019385609518437, -0.4450484640237961, 0.0, 0.4450484640237961, 0.8019385609518437, 1.0]
weight = [1.309924793995232e7, 1.311697371095455e7, 1.31290303653434e7, 1.3134417169089135e7, 7.300760397632944e6, 296.9188842891679, 1.0]
invy = [7.634026049312568e-8, 7.623709721739069e-8, 7.61670871475545e-8, 7.613584882574196e-8, 1.369720338068101e-7, 0.003367923203652162, 1.0]
p = [0.0, 0.021220788737679505, 0.4893496181966227, -0.27747890271555137]


opt = Opt(:LD_SLSQP, 4)
opt.lower_bounds = [-Inf, 0, 0, -Inf]
opt.ftol_rel = 1e-3

function myfunc(p::Vector, grad::Vector)
    p[2] < 0 && (p[2] = 0)
    p[3] < 0 && (p[3] = 0)
    Δ = sqrt.(p[2] .+ p[3]*(ξ.-p[4]).^2)
    f = p[1] .+ Δ
    objf = (invy .- f) .* weight
    if length(grad) > 0 # do not use isempty(grad)
        grad[1] =       -2sum(objf                      .* weight)
        grad[2] =        -sum(objf                 ./ Δ .* weight)
        grad[3] =        -sum(objf .* (ξ.-p[4]).^2 ./ Δ .* weight)
        grad[4] = 2p[3] * sum(objf .* (ξ.-p[4])    ./ Δ .* weight)
    end
    sum(abs2, objf)
end

opt.min_objective = myfunc
(minf, minx, ret) = optimize(opt, p)

NLopt v1.0.2 and Julia 1.10.3.