# Function to optimize doesn't converge in conjugate gradient and quasi newton

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farzad 2021 年 3 月 29 日
コメント済み: farzad 2021 年 4 月 1 日
Hi all
I have a function as :
f(x) = x1^2 + x2^2 + 2x3^2 - x4^2 - 5x1 - 5x2 -21x3 + 7x4 +100
subject to
x1^2 + x2 ^2+x3 ^2 +x4 ^2 +x1-x2+x3-x4 - 100 <= 0
x1 ^2+2 x2 ^2+ x3^2+ 2 x^4 - x1 - x4 -10 <= 0
2x1 ^2 + x2 ^2 + x3^2 + 2x1 - x2 - x4 - 5 <=0
-100 <= xi <= 100 , i = 1,2,3,4
I tried with quasi newton and Conjugate gradient, but I don't succeed.
How could I improve it and what is the problem ? I attached my codes too
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John D'Errico 2021 年 4 月 1 日
Just looking quickly at your objective...
You have a non-convex function. The -x4^2 term suggests that any solution will probably fall on a boundary, though I will not assert that to be fact without considerably more thought invested. Your boundaries are simple ones that will look like hyper-ellipses, so the intersection of those boundaries tells me the solution will be well posed. But, as I said, the solution wil probably be on a boundary. That means at least one or more of those constraints will be active.
When you say it is not converging, what does that mean to you? Why do you think it is not converging?
farzad 2021 年 4 月 1 日
Since it converges without the boundaries with a certain step size I thought it's due to the boundaries

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