Speed up fminbnd using vectorization

Question

Luca Gagliardone 2017-8-12

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https://ww2.mathworks.cn/matlabcentral/answers/352527-speed-up-fminbnd-using-vectorization

编辑： Matt J 2018-5-24

I am trying to optimize this piece of code. I am using the function fminbnd on a vector, splitting the task on its single entries using a loop.

Would it be possible to speed it up vectorizing the process?

        for i = 1:A
            for ii= 1:B
                for iii = 1:C
                    fun = @(x) (x * variable(i,ii,iii))^2 ;
                    [arg_min(i,ii,iii), min_(i,ii,iii)] = fminbnd(fun,0,2);
                end
            end
        end

Thanks for the attention.

Sincerely

Luca

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Answer 1

Matt J 2017-8-12

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In your example, the solution is always x=0, so a trivial vectorized solution would be

arg_min=zeros(A,B,C);
min_ = arg_min;

More generally, no, vectorization will not help in a situation like this. You could consider parallelizing the loop using PARFOR.

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Answer 2

Luca Gagliardone 2017-8-16

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https://ww2.mathworks.cn/matlabcentral/answers/352527-speed-up-fminbnd-using-vectorization#answer_278134

编辑：Luca Gagliardone 2017-8-16

在 MATLAB Online 中打开

What if I create a vector x containing all the possible values for minimization:

x = permute(repmat([0:0.01:2]',[1,A,B,C]),[2,3,4,1]);
variable2 = repmat(variable,[1,1,1,length(x)]);
fun = (x .* variable2).^2;
min_ = min(fun,[],4);

That would do an approximation of the above? Thanks.

Luca