Fast Makespan Minimization via Short ILPs

TL;DR

This paper leverages recent advances in solving short integer linear programs to develop faster algorithms for makespan minimization on a fixed number of machines, significantly improving efficiency for moderate processing times.

Contribution

It introduces new pseudo-polynomial algorithms for makespan minimization using short ILP solver improvements, enhancing previous time complexity bounds.

Findings

Algorithms run in tilde;O(p_{\u2215max}^{O(1)}+n) or tilde;O(p_{\u2215max}^{O(1)} imes n) time.

Significant speedup over previous algorithms for moderate p_{max}.

Applicable to related scheduling variants.

Abstract

Short integer linear programs are programs with a relatively small number of constraints. We show how recent improvements on the running-times of solvers for such programs can be used to obtain fast pseudo-polynomial time algorithms for makespan minimization on a fixed number of parallel machines, and other related variants. The running times of our algorithms are all of the form $\widetilde{O}(p^{O(1)}_{\max}+n)$ or $\widetilde{O}(p^{O(1)}_{\max} \cdot n)$, where $p_{\max}$ is the maximum processing time in the input. These improve upon the time complexity of previously known algorithms for moderate values of $p_{\max}$.