error surrogateopt: At least objective or constraints function must be non-empty

For my integer global optimization problem I'm using surrogateopt. The code was working before but something changed and it gives me an error now that I haven't been able to solve. I'm using matlab2023a. The errors are as follows:

Error using globaloptim.bmo.BlackboxModelOptimizer/optimize

At least objective or constraints function must be non-empty.

Error in surrogateopt (line 375)

controller = controller.optimize();

Error in Grid_calculation2_new (line 205)

optimdesign = surrogateopt(@(x) Surrogate_optimization_target(wl, ...

For my problem I have no constraints except the upper and lower bounds. The objective is specified in surrogateopt() as has also been done in this example: https://nl.mathworks.com/help/gads/surrogate-optimization-antenna-design.html

Here is part the part of the code that I expect to be relevant for this error. I hope someone can help me solve this error.

values_repeats_LB = zeros(1,size(structure_variaties,2));
values_repeats_UB = zeros(1,size(structure_variaties,2));
for i=1:size(structure_variaties,2)
    values_repeats_LB(i) = structure_variaties{2,i}(1);
    values_repeats_UB(i) = structure_variaties{2,i}(end);
end

%Lower and upper bounds values follow same order as variable materials
materials = [silica, TiO2, YAG]; %[silica, TiO2, YAG];
Lower_bounds = [60 40 100]; %Set the lower bounds here in nanometer
Upper_bounds = [120 120 300]; %Set the upper bounds here in nanometer
multiply_factor = 5; %E.g. vary the thickness per 5nm when choosing 5.
LB = [Lower_bounds/multiply_factor values_repeats_LB];
UB = [Upper_bounds/multiply_factor values_repeats_UB];
intcon = 1:size(LB,2);
plots_or_not = 0; %No plots
em_or_ex = 0; %Excitation (0) not emission (1)
%target_options = ["avg field ex" "avg abs ex" "avg field em" ...
%    "tot em field" "plus PL" ...
%    "plus transmission" "CRI" "factor"]; %options for for output_choice
target_choice = ["tot em field"]; %what you want as output. 
surrogateoptions = optimoptions('surrogateopt', ...
    'MaxFunctionEvaluations',500, ... 
    'UseParallel',false, ...
    'PlotFcn','surrogateoptplot');
rng(4) % Fix randomness for reproducibility
optimdesign = surrogateopt(@(x) Surrogate_optimization_target(wl, ...
    op_wl_ex, op_wl_em, theta, data_file, angle, z_step_size, ...
    plots_or_not, em_or_ex, target_choice, ...
    multiply_factor, basis_model, structure_variaties, materials, x), ...
    LB, UB, intcon, surrogateoptions);
best_parameters = optimdesign;
best_parameters(1:3) = best_parameters(1:3)*multiply_factor;

[Matt J]

Here is part the part of the code that I expect to be relevant for this error

No, I don't think so. We need to see the code for Surrogate_optimization_target and we need a .mat file (just one) containing all the variables in this line,

optimdesign = surrogateopt(@(x) Surrogate_optimization_target(wl, ...
    op_wl_ex, op_wl_em, theta, data_file, angle, z_step_size, ...
    plots_or_not, em_or_ex, target_choice, ...
    multiply_factor, basis_model, structure_variaties, materials, x), ...
    LB, UB, intcon, surrogateoptions);

[René Bruikman]

Thank you for your reaction Matt. After a good night of rest and during the process of uploading the rest of my code I've figured out where it went wrong, unfortunately I was unable to catch the small error during the entire previous afternoon. The function Surrogate_optimization_target() that I made had no ouput value, the variable it outputs was empty e.g. [ ]. Something went wrong with the definition of the output inside that function, resulting in the calculated value not being assigned to the output parameter. After solving this issue the code and global optimization is working.