  The integer complexity $f(n)$ of a positive integer $n$ is defined as the
minimum number of 1's needed to represent $n$, using additions, multiplications
and parentheses. We present two simple and faster algorithms for computing the
integer complexity:
  1) A near-optimal $O(N\mathop{\mathrm{polylog}} N)$-time algorithm for
computing the integer complexity of all $n\leq N$, improving the previous
$O(N^{1.223})$ one [Cordwell et al., 2017].
  2) The first sublinear-time algorithm for computing the integer complexity of
a single $n$, with running time $O(n^{0.6154})$. The previous algorithms for
computing a single $f(n)$ require computing all $f(1),\dots,f(n)$.
