On the Configuration-LP of the Restricted Assignment Problem

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 $\mathrm{P} = \mathrm{NP}$.