  Let $\mu(G)$ denote the minimum number of edges whose addition to $G$ results
in a Hamiltonian graph, and let $\hat{\mu}(G)$ denote the minimum number of
edges whose addition to $G$ results in a pancyclic graph. We study the
distributions of $\mu (G),\hat{\mu}(G)$ in the context of binomial random
graphs. Letting $d=d(n)$:=$n\cdot p$, we prove that there exists a function
$f:\mathbb{R}^+\to [0,1]$ of order $f(d) =
\frac{1}{2}de^{-d}+e^{-d}+O(d^6e^{-3d})$ such that, if $G\sim G(n,p)$ with $20
\le d(n) \le 0.4 \log n$, then with high probability $\mu (G)= (1+o(1))\cdot
f(d)\cdot n$. Let $n_i(G)$ denote the number of degree $i$ vertices in $G$. A
trivial lower bound on $\mu(G)$ is given by the expression $n_0(G) + \lceil
\frac{1}{2}n_1(G) \rceil$. We show that in the random graph process $\{
G_t\}_{t=0}^{\binom{n}{2}}$ with high probability there exist times $t_1,t_2$,
both of order $(1+o(1))n\cdot \left( \frac{1}{6}\log n + \log \log n \right)$,
such that $\mu(G_t)=n_0(G_t) + \lceil \frac{1}{2}n_1(G_t) \rceil$ for every
$t\ge t_1$ and $\mu(G_t)>n_0(G_t) + \lceil \frac{1}{2}n_1(G_t) \rceil$ for
every $t\le t_2$. The time $t_i$ can be characterized as the smallest $t$ for
which $G_t$ contains less than $i$ copies of a certain problematic subgraph. In
particular, this implies that the hitting time for the existence of a Hamilton
path is equal to the hitting time of $n_1(G) \le 2$ with high probability. For
the binomial random graph, this implies that if $np-\frac{1}{3}\log n - 2\log
\log n \to \infty$ and $G\sim G(n,p)$ then, with high probability, $\mu (G) =
n_0(G) + \lceil \frac{1}{2}n_1(G) \rceil$. Finally, we show that if $G\sim
G(n,p)$ and $np\ge 20$ then, with high probability, $\hat{\mu} (G)=\mu (G)$.
