I'm studying algorithm complexity and I am trying to figure out this one question that runs in my mind- is O(n!) faster than O(2^n) or is it the opposite way around?
I'm studying algorithm complexity and I am trying to figure out this one question that runs in my mind- is O(n!) faster than O(2^n) or is it the opposite way around?
O(2^n) is 2 * 2 * 2 * ... where O(n!) is 1 * 2 * 3 * 4 * ...
O(n!) will quickly grow much larger - so O(2^n) is faster.
For example: 2^10 = 1024 and 10! = 3628800
You can try working with Stirling's approximation for n!
https://en.wikipedia.org/wiki/Stirling%27s_approximation
n! = (n / e)^n * sqrt(2 * Pi * n) * (1 + o(n))
Now, let's compare
O(n!) <=> O(2^n)
In order to find out the right letter <, = or > let's compute limit
lim (n! / 2^n) =
n -> +inf
lim (n / e)^n * sqrt(2 * pi * n) / 2^n >=
n -> +inf
lim n^n / (2 * e)^n >= // when n > 4 * e
n -> +inf
lim (4 * e)^n / (2 * e)^n =
n -> +inf
lim 2^n = +inf
n -> +inf
So
lim (n! / 2^n) = +inf
n -> +inf
which means that O(n!) > O(2^)