Saving GAmultiobj results calculated in the algorithm mid-way, without stopping the code run.

21 vues (au cours des 30 derniers jours)
I am running a GAmultiobj optimization code with 2 objective functions and 21 input variables. The code takes a long time to run and crashes in between (due to some bug which I am trying to fix).
I am plotting the Pareto-Front of the 2 objectives with default settings. I am able to see the points on the Pareto-Front which tell me the values of the 2 objectives (fval) if I pause my code (say 20 such points). However, I want to also know the variable (xval) values for those points on the Pareto-Front (20-by-21 array), even when the optimization algorithm has not completed. This way atleast some of the variable values will be available to me even if the code crashes later.
I have kept the 'UseParallel' setting to 'true'. What I have tried so far:
  1. Include an 'OutputFcn' command to keep storing the 'Population' and respective 'Scores'. However, those values do not correspond to the points currently being displayed on the Pareto-Front.
  2. Tried the solution posted in this thread but I am unable to find the results (xval and fval) which have been calculated so far in any of the debugger files. Is this because I am using Parallel setting which is causing the input space to get split up ?
Any help would be really appreciated!

Réponses (1)

Swastik Sarkar
Swastik Sarkar le 21 Nov 2024 à 7:09
I was able to use OutputFcn to display the Pareto-front values fval and corresponding x, achieving this with the following output function:
function [state, options, optchanged] = dispParetoFront(options, state, flag)
optchanged = false;
if isequal(flag, 'iter')
topRankedIdx = state.Rank == 1;
fval = state.Score(topRankedIdx,:);
x = state.Population(topRankedIdx,:);
disp(fval);
disp(x);
end
end
In the code above, fval corresponds to the values being plotted. Below is the corresponding plot:
Please refer to the below plot for one such iteration:
Following is the output of the OutputFcn for that iteration:
Average Average
Generation Func-count Pareto distance Pareto spread
1 100 1 1
175.7636 213.0926
222.3589 202.6253
207.0830 206.5507
Columns 1 through 12
5.3488 0.6370 0.1491 -0.5133 0.2020 -1.0246 2.5131 0.3995 -0.9634 -5.1355 3.5102 2.6572
-1.5666 1.8390 -4.4555 0.8624 -4.0777 4.5399 4.5765 -2.3334 1.2334 2.1562 3.3867 -3.2181
4.9653 -0.0933 -3.4053 3.1967 -0.6689 3.4599 -0.0144 -5.6348 -1.9415 -0.6209 2.1915 0.5244
Columns 13 through 21
1.5702 -4.9496 -2.0260 -1.5951 -0.1794 -6.9090 -1.8514 -1.9264 1.9222
1.6208 1.9597 -0.6533 2.3225 0.6406 -2.3525 7.0044 0.8590 6.0227
-1.0549 4.7118 0.7702 -0.2536 -0.7465 -4.6771 0.1338 7.3640 2.5598
Hope this works for you.

Catégories

En savoir plus sur Get Started with Optimization Toolbox dans Help Center et File Exchange

Produits


Version

R2024a

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by