How to exploit convexity of y^2 over x in yalmip ?

[JackJack]

Dear Professor Johan Lofbeg,

I am currently working on a problem where I need to model the function f(x, y) = y^2/x, where x is strictly positive (x > 0). Based on an analysis of its Hessian, I've confirmed that this function is convex.

I am trying to determine if there is a built-in function or a recommended method within YALMIP that can help exploit this convexity directly for modeling purposes, particularly since y^2/x is a non-standard form. I searched on the YALMIP homepage but was unable to find specific guidance related to this particular function.

Any direction or advice you could offer on the best way to handle this modeling would be greatly appreciated.

Thank you very much for your time and assistance.

[Johan Löfberg]

>> help quadratic_over_affine
 quadratic_over_affine (overloaded)
 
  p = quadratic_over_affine(x,t)
 
  Returns p = (x.^2)./t

>>

but much better to understand that you write x^2/y < =t as x^2<ty which you write as socp manually 

[JackJack]

Thank you I understand it now