Optimizing a function from a given set?
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Is there a way to find the optimal value of a minimized function from a given set of solutions?
Here is an example of what I would like to do:
For x in {0,0.5,1}, solve: x = arg max f(x).
I think I would need a variation of "fminbnd", as this one uses a given interval of solutions, while I need a given set of solutions.
Any suggestion would be very much appreciated. Thank you
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Walter Roberson
2018-6-17
For an explicit list of arguement values, x:
[bestfval, bestidx] = max(arrayfun(@f, x))
bestx = x(bestidx);
If the function is fully vectorized then
[bestfval, bestidx] = max(f(x(:)));
bestx = x(bestidx);
2 个评论
Mohamed Larabi
2018-6-17
Walter Roberson
2018-6-17
If the task is to find the y that maximizes x*f(y) for each given x, then the answer is going to be the same as the y that maximizes f(y) without considering the x because multiplication by positive x is a linear operator. If some of the x could be negative and some positive then you could have a more interesting situation.
更多回答（1 个）
Mohamed Larabi
2018-6-17
0 个投票
1 个评论
Walter Roberson
2018-6-17
If f(y) is given, then the x that maximizes x*f(y) is:
if f(y) > 0
bestx = max(x);
elseif f(y) < 0
bestx = min(x);
else
all finite non-nan entries in x give the same result
end
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