A (1+epsilon)-Approximation for Makespan Scheduling with Precedence Constraints using LP Hierarchies

TL;DR

This paper introduces a novel LP-hierarchy based approach that achieves a near-optimal approximation for the makespan scheduling problem with precedence constraints, resolving a long-standing open problem for fixed number of machines.

Contribution

It demonstrates that a small number of LP-hierarchy rounds can yield a (1+ε)-approximation for the scheduling problem, improving upon previous polynomial-time algorithms.

Findings

Achieves (1+ε)-approximation using LP hierarchies.

Applicable for fixed number of machines m and any ε>0.

Improves approximation ratio from 2 to near-optimal for certain cases.

Abstract

In a classical problem in scheduling, one has $n$ unit size jobs with a precedence order and the goal is to find a schedule of those jobs on $m$ identical machines as to minimize the makespan. It is one of the remaining four open problems from the book of Garey & Johnson whether or not this problem is $\mathbf{NP}$-hard for $m=3$. We prove that for any fixed $\varepsilon$ and $m$, an LP-hierarchy lift of the time-indexed LP with a slightly super poly-logarithmic number of $r = (\log(n))^{\Theta(\log \log n)}$ rounds provides a $(1 + \varepsilon)$-approximation. For example Sherali-Adams suffices as hierarchy. This implies an algorithm that yields a $(1+\varepsilon)$-approximation in time $n^{O(r)}$. The previously best approximation algorithms guarantee a $2 - \frac{7}{3m+1}$-approximation in polynomial time for $m \geq 4$ and $\frac{4}{3}$ for $m=3$. Our algorithm is based on a recursive scheduling approach where in each step we reduce the correlation in form of long chains. Our method adds to the rather short list of examples where hierarchies are actually useful to obtain better approximation algorithms.