Optimization function break and start over with new dataset

I have a Surrogate optimization program which is searching for the optimal workpiece position on the table. It searches only x, y and rotation angle around z-axis (3 variables).

% SURROGATE OPTIMIZATION
clear;clc; rng default
lb = [-0.34,-0.85,0];
ub = [0.34,-0.25,360];
A = []; b = []; Aeq = []; beq = []; intcon = [];
nvars = 3;

options = optimoptions('surrogateopt','PlotFcn','surrogateoptplot');
[xopt,fval,exitflag,output] = surrogateopt(@ManipulabilityFun,lb,ub,intcon,A,b,Aeq,beq,options);

And then I have this optimization function:

% Optimization setup
load ('T.mat');
xos=xopt(1);
yos=xopt(2);
rotz=xopt(3);

Z = -0.095845; %Z is fixed
rot=trotz(rotz,'deg');
TWtoB_org= [1.000000, 0.000000, 0.000000, xos; %X
            0.000000, 1.000000, 0.000000, yos; %Y
            0.000000, 0.000000, 1.000000, Z; %Z(fixed)
            0.000000, 0.000000, 0.000000, 1.000000]; %Horizontal Option1

TWtoB_org=TWtoB_org*rot;
TPtoB=pagemtimes(TWtoB_org,T);

%% REACHABILITY
n2=0;
for b=1:size(TPtoB1,4)
    n2=n2+1;
    q1=ur5_kin.inverse_kinematics(TPtoB1(:,:,:,n2)*Ttransl, 0);
    if isempty(q1)
        q=zeros(1,6);
    else
        for c=1:size(q1,1)
            config=conf_func(q1(c,:));
            if config(1) == 1 && config(2) == 0 && config(3) == 1
                q=q1(c,:);
            end
        end
        if exist ('q','var')~=1
            q=zeros(1,6);
        end
    end
         Sol1(n2,:)=[q];
         clearvars q q1
         S1=find(Sol1(:,1)==0);
         S2=n2-size(S1,1);
         Part_reach1=-S2/size(TPtoB,4)*100; %Reachability of part - NEGATIVE FOR OPTIMIZATION
end

if Part_reach1 ~=-100 %IF reachability is not 100% set joint values to 0
    Sol2=zeros(size(Sol2,1),6);
end

If I understand correctly optimization program generates random n variables for x y and rotation angle which are then put into the optimization function. Some random values that surrogate optimization generators are not optimal and I am solving this with some kind of weights like here:

if Part_reach1 ~=-100 %IF reachability is not 100% set joint values to 0
    Sol2=zeros(size(Sol2,1),6);
end

So if based on the input data (workpiece position), not all the points on the workpiece in that position are reachable I am changing all solutions to zeros to lower the average value. I need to do this because the program goes further and in the next step I am using this artificially lowered values. This has become difficult to navigate throughout the program and I am starting to have problems (Code smell).

My question is: When condition in optimization function is not satisfied, how can I break the program so it goes completely from beginning and starts with new data?

Answer 1

[Anurag]

Hi RoboTomo,

I understand that you want your loop to break and carryon with your other existing variables if the process of optimisation is not met. Please refer the code below to help you address this issue.

% Surrogate Optimization Parameters

lb = [-0.34, -0.85, 0];
ub = [0.34, -0.25, 360];
A = []; b = []; Aeq = []; beq = []; intcon = [];
nvars = 3;

options = optimoptions('surrogateopt', 'PlotFcn', 'surrogateoptplot');

% Loop for optimization
while true
    
    % Optimization
    [xopt, fval, exitflag, output] = surrogateopt(@ManipulabilityFun, lb, ub, intcon, A, b, Aeq, beq, options);  
    % Your optimization function
    load('T.mat');
    xos = xopt(1);
    yos = xopt(2); 
    rotz = xopt(3);
       
    % Check your condition (e.g., reachability)
    if Part_reach1 ~= -100
        % Restart optimization by breaking the loop
        break; 
    end
    % Continue with your optimization process
    % ...  
    % Optionally, update lb and ub based on previous solutions
    % lb = ...;
    % ub = ...;
    
end

Hope this helped,

Regards,

Anurag