Parallel Gradient Based Optimizer, Objective Function Uses Simulink
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Hello,
I am working on an optimization problem. I currently have a simulink model what I would like to do is to find the right parameters in the Simulink model so that the results it gives matches the test data.
I have managed to use ga, with UseVectorized=true to parallelize it, my objective function calls simulink model to calculate the error between test data and simulation results. What I would like to do is the same but I want to use a gradient based optimizer like fmincon, but I could not make it work. Can anyone explain how to do this with fmincon, there is no UseVectorized option. Any other gradient based optimizer can also work.
Kind Regards
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Ayush Aniket
2024-11-14
编辑：Ayush Aniket
2024-11-14
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Hi Sadi,
I understand that your objective is to use gradient based optimization function like fmincon with parallel computing options. You can use the UseParallel argument of the optimoptions funtion and then supply it to the fmincon function. Refer to the following documentation link that shows an example for the same: https://www.mathworks.com/help/optim/ug/minimizing-an-expensive-optimization-problem-using-parallel-computing-toolbox.html#d126e83518
Also, you can read about the optimoptions function here: https://www.mathworks.com/help/optim/ug/optim.problemdef.optimizationproblem.optimoptions.html
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