We consider the class of random matrices $C=(c_{ij})$, $i,j=1,\dots,N$,
whose elements are independent random variables distributed by the same law as
a certain random variable $\xi$ such that $\mathsf E\xi^2>0$. As usual,
$\operatorname{per}C$ stands for the permanent of the matrix $C$. In the triangular array series where
$\xi=\xi_N$, $\mathsf E\xi_N\neq 0$, $N=1,2,\dotsc$, $\mathsf D\xi_N=o((\mathsf E\xi_N)^2)$ as
$N\to\infty$, we prove that the sequence of random variables
$\operatorname{per}C/(N!\,(\mathsf E\xi_N)^N)$ converges in probability to one as $N\to \infty$.
A similar result is shown to be true in a more general case where the rows of the matrix
$C$ are independent $N$-dimensional random vectors which have the same distribution
coinciding with the distribution of a random vector $\mu$ whose components
are identically distributed but are, generally speaking, dependent.
We give sufficient conditions for the law of large numbers to be true
for the sequence $\operatorname{per}C/\mathsf E\operatorname{per}C$ in the cases where the vector
$\mu$ coincides with the vector of frequencies of outcomes of
the equiprobable polynomial scheme
with $N$ outcomes and $n$ trials and also where $\mu$
is a random equiprobable solution of the equation
$k_1+\ldots+k_N=n$ in non-negative integers $k_1,\dots,k_N$.