Why easier to numerically minimize than to maximize a function

Question

Is it easier, in terms of coputational complexity or speed, to numerically minimize a function $f$ than to maximize $-f$? Why is that so? I have noticed that most optimization algorithms in Matlab are written to minimize the input, and I have been told that it is indeed more efficient to do so.

Answer 1

What was told to you is simply nonsense. As given in the comment by par, maximization is the mirror of minimization with respect to multiplication by $-1$. The function does not get any simpler or more complex by multiplying it by $-1$. Therefore maximization and minimization are of equivalent complexity.