  We consider the classical problem of Scheduling on Unrelated Machines. In
this problem a set of jobs is to be distributed among a set of machines and the
maximum load (makespan) is to be minimized. The processing time $p_{ij}$ of a
job $j$ depends on the machine $i$ it is assigned to. Lenstra, Shmoys and
Tardos gave a polynomial time $2$-approximation for this problem. In this paper
we focus on a prominent special case, the Restricted Assignment problem, in
which $p_{ij}\in\{p_j,\infty\}$. The configuration-LP is a linear programming
relaxation for the Restricted Assignment problem. It was shown by Svensson that
the multiplicative gap between integral and fractional solution, the
integrality gap, is at most $2 - 1/17 \approx 1.9412$. In this paper we
significantly simplify his proof and achieve a bound of $2 - 1/6 \approx
1.8333$. As a direct consequence this provides a polynomial $(2 - 1/6 +
\epsilon)$-estimation algorithm for the Restricted Assignment problem by
approximating the configuration-LP. The best lower bound known for the
integrality gap is $1.5$ and no estimation algorithm with a guarantee better
than $1.5$ exists unless $\mathrm{P} = \mathrm{NP}$.
