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Using optimization Toolbox without Objective functions, only set of points

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omid rastkhiz paydar
omid rastkhiz paydar 15 Feb 2021
댓글: Walter Roberson 16 Feb 2021
I have 4 or 5 input parameters and 1 or 2 output parameters and these inputs and outputs are only points and there is no function, e.g. 3 inputs and 2 outputs, like 10,6,26 inputs and 0.11 , 0.16 as two outputs and in total I have 10 of these set of points (each set has 3 inputs and 2 outputs) and also a simple constraint for each parameter like (a < x1,x2,x3 < b) and now I want to find a combination of these 3 inputs that the sum of my outputs would be less than 0.1, and I want to use e.g. Genetic Algorithm, so it is a possibility that I have several answers or sets of 3 inputs, and that is ok (acceptable) in my case. and Basiclly it is an improvement instead of optimization.
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Walter Roberson
Walter Roberson 16 Feb 2021
If you want to minimize stress, and stress is returned by that 10*log10 calculation, then do that 10*log10 calculation and return that.

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Matt J
Matt J 15 Feb 2021
편집: Matt J 15 Feb 2021
in total I have 10 of these set of points
You are minimizing over a small, finite set of things. Just use min().
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Walter Roberson
Walter Roberson 16 Feb 2021
Sum of squares of errors is a scalar that can be returned, and that effectively is the objective function.
Objective functions do not need to be mathematical formulas.
(However, the minimizers might not work correctly if whatever is calculated is not continuous in the parameters.)
If the call to ANSYS is "expensive" then you should have a look at surrogate optimization.

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