fmincon rough estimation in little time

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Federico Spada
Federico Spada 2018년 11월 6일
댓글: Federico Spada 2018년 11월 6일
I have a simulink model with some parameters and i want to find the minimum of an objective function. The problem is that i should run the minimization for many times varying the objective function itself, but with normal settings it takes me 7,5 min to get only one estimation, too much if i need 100 of them. But the good thing is that i don't need a good precision in finding the minimum, some variables could be integer but fmincon doesn't allow to specify that. So i decided to relax some tolerances, in particolar StepTolerance. The problem is that at the start of simulation the step size is very small and this force me to set a bigger StepTolerance than needed. So i thought that maybe there was a method to impose a minimum step size and so i found FiniteDifferenceStepSize and DiffMinChange but in any way i set them, the inizial step size is in the order of e-3 but i would like it to be 1 or even bigger so that i can set StepTolerance to 1.
Regardless of what i wrote until now, can you suggest me a way to speed up my estimation so that i can get close to a minimun with a precision that i can choose? Maybe i'm not using correctly the previous options or maybe there is a better way to do the entire thing. Thanks in advance,
Federico Spada

답변 (1개)

John D'Errico
John D'Errico 2018년 11월 6일
fmincon is pretty much the wrong tool for this for multiple reasons. It is not designed to allow for low precision. It certainly is not designed to allow for integer parameters.
Instead, you might start looking here:
https://tomopt.com/docs/cgo/tomlab_cgo007.php
Thus an optimization tool designed for costly objective functions.
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Federico Spada
Federico Spada 2018년 11월 6일
But the problem is that it's not free... What do those options do if it seems that they have no influence on the estimation?

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